2011-04-08 Joel Sherrill <joel.sherrill@oarcorp.com>

	* AUTHORS, BUGS, COPYING, ChangeLog, INSTALL, Makefile.am, Makefile.in,
	NEWS, README, SUPPORT, THANKS, TODO, acconfig.h, aclocal.m4,
	autogen.sh, config.guess, config.h.in, config.sub, configure,
	configure.ac, gsl-config.in, gsl-histogram.c, gsl-randist.c, gsl.m4,
	gsl.pc.in, gsl.spec.in, gsl_machine.h, gsl_math.h, gsl_mode.h,
	gsl_nan.h, gsl_pow_int.h, gsl_precision.h, gsl_types.h,
	gsl_version.h.in, install-sh, ltmain.sh, mdate-sh, missing,
	mkinstalldirs, templates_off.h, templates_on.h,
	test_gsl_histogram.sh, version.c, blas/ChangeLog, blas/Makefile.am,
	blas/Makefile.in, blas/TODO, blas/blas.c, blas/gsl_blas.h,
	blas/gsl_blas_types.h, block/ChangeLog, block/Makefile.am,
	block/Makefile.in, block/block.c, block/block_source.c, block/file.c,
	block/fprintf_source.c, block/fwrite_source.c, block/gsl_block.h,
	block/gsl_block_char.h, block/gsl_block_complex_double.h,
	block/gsl_block_complex_float.h,
	block/gsl_block_complex_long_double.h, block/gsl_block_double.h,
	block/gsl_block_float.h, block/gsl_block_int.h,
	block/gsl_block_long.h, block/gsl_block_long_double.h,
	block/gsl_block_short.h, block/gsl_block_uchar.h,
	block/gsl_block_uint.h, block/gsl_block_ulong.h,
	block/gsl_block_ushort.h, block/gsl_check_range.h, block/init.c,
	block/init_source.c, block/test.c, block/test_complex_io.c,
	block/test_complex_source.c, block/test_io.c, block/test_source.c,
	bspline/ChangeLog, bspline/Makefile.am, bspline/Makefile.in,
	bspline/TODO, bspline/bspline.c, bspline/gsl_bspline.h,
	bspline/test.c, cblas/ChangeLog, cblas/Makefile.am,
	cblas/Makefile.in, cblas/TODO, cblas/caxpy.c, cblas/cblas.h,
	cblas/ccopy.c, cblas/cdotc_sub.c, cblas/cdotu_sub.c, cblas/cgbmv.c,
	cblas/cgemm.c, cblas/cgemv.c, cblas/cgerc.c, cblas/cgeru.c,
	cblas/chbmv.c, cblas/chemm.c, cblas/chemv.c, cblas/cher.c,
	cblas/cher2.c, cblas/cher2k.c, cblas/cherk.c, cblas/chpmv.c,
	cblas/chpr.c, cblas/chpr2.c, cblas/cscal.c, cblas/csscal.c,
	cblas/cswap.c, cblas/csymm.c, cblas/csyr2k.c, cblas/csyrk.c,
	cblas/ctbmv.c, cblas/ctbsv.c, cblas/ctpmv.c, cblas/ctpsv.c,
	cblas/ctrmm.c, cblas/ctrmv.c, cblas/ctrsm.c, cblas/ctrsv.c,
	cblas/dasum.c, cblas/daxpy.c, cblas/dcopy.c, cblas/ddot.c,
	cblas/dgbmv.c, cblas/dgemm.c, cblas/dgemv.c, cblas/dger.c,
	cblas/dnrm2.c, cblas/drot.c, cblas/drotg.c, cblas/drotm.c,
	cblas/drotmg.c, cblas/dsbmv.c, cblas/dscal.c, cblas/dsdot.c,
	cblas/dspmv.c, cblas/dspr.c, cblas/dspr2.c, cblas/dswap.c,
	cblas/dsymm.c, cblas/dsymv.c, cblas/dsyr.c, cblas/dsyr2.c,
	cblas/dsyr2k.c, cblas/dsyrk.c, cblas/dtbmv.c, cblas/dtbsv.c,
	cblas/dtpmv.c, cblas/dtpsv.c, cblas/dtrmm.c, cblas/dtrmv.c,
	cblas/dtrsm.c, cblas/dtrsv.c, cblas/dzasum.c, cblas/dznrm2.c,
	cblas/gsl_cblas.h, cblas/hypot.c, cblas/icamax.c, cblas/idamax.c,
	cblas/isamax.c, cblas/izamax.c, cblas/sasum.c, cblas/saxpy.c,
	cblas/scasum.c, cblas/scnrm2.c, cblas/scopy.c, cblas/sdot.c,
	cblas/sdsdot.c, cblas/sgbmv.c, cblas/sgemm.c, cblas/sgemv.c,
	cblas/sger.c, cblas/snrm2.c, cblas/source_asum_c.h,
	cblas/source_asum_r.h, cblas/source_axpy_c.h, cblas/source_axpy_r.h,
	cblas/source_copy_c.h, cblas/source_copy_r.h, cblas/source_dot_c.h,
	cblas/source_dot_r.h, cblas/source_gbmv_c.h, cblas/source_gbmv_r.h,
	cblas/source_gemm_c.h, cblas/source_gemm_r.h, cblas/source_gemv_c.h,
	cblas/source_gemv_r.h, cblas/source_ger.h, cblas/source_gerc.h,
	cblas/source_geru.h, cblas/source_hbmv.h, cblas/source_hemm.h,
	cblas/source_hemv.h, cblas/source_her.h, cblas/source_her2.h,
	cblas/source_her2k.h, cblas/source_herk.h, cblas/source_hpmv.h,
	cblas/source_hpr.h, cblas/source_hpr2.h, cblas/source_iamax_c.h,
	cblas/source_iamax_r.h, cblas/source_nrm2_c.h, cblas/source_nrm2_r.h,
	cblas/source_rot.h, cblas/source_rotg.h, cblas/source_rotm.h,
	cblas/source_rotmg.h, cblas/source_sbmv.h, cblas/source_scal_c.h,
	cblas/source_scal_c_s.h, cblas/source_scal_r.h, cblas/source_spmv.h,
	cblas/source_spr.h, cblas/source_spr2.h, cblas/source_swap_c.h,
	cblas/source_swap_r.h, cblas/source_symm_c.h, cblas/source_symm_r.h,
	cblas/source_symv.h, cblas/source_syr.h, cblas/source_syr2.h,
	cblas/source_syr2k_c.h, cblas/source_syr2k_r.h,
	cblas/source_syrk_c.h, cblas/source_syrk_r.h, cblas/source_tbmv_c.h,
	cblas/source_tbmv_r.h, cblas/source_tbsv_c.h, cblas/source_tbsv_r.h,
	cblas/source_tpmv_c.h, cblas/source_tpmv_r.h, cblas/source_tpsv_c.h,
	cblas/source_tpsv_r.h, cblas/source_trmm_c.h, cblas/source_trmm_r.h,
	cblas/source_trmv_c.h, cblas/source_trmv_r.h, cblas/source_trsm_c.h,
	cblas/source_trsm_r.h, cblas/source_trsv_c.h, cblas/source_trsv_r.h,
	cblas/srot.c, cblas/srotg.c, cblas/srotm.c, cblas/srotmg.c,
	cblas/ssbmv.c, cblas/sscal.c, cblas/sspmv.c, cblas/sspr.c,
	cblas/sspr2.c, cblas/sswap.c, cblas/ssymm.c, cblas/ssymv.c,
	cblas/ssyr.c, cblas/ssyr2.c, cblas/ssyr2k.c, cblas/ssyrk.c,
	cblas/stbmv.c, cblas/stbsv.c, cblas/stpmv.c, cblas/stpsv.c,
	cblas/strmm.c, cblas/strmv.c, cblas/strsm.c, cblas/strsv.c,
	cblas/test.c, cblas/test_amax.c, cblas/test_asum.c,
	cblas/test_axpy.c, cblas/test_copy.c, cblas/test_dot.c,
	cblas/test_gbmv.c, cblas/test_gemm.c, cblas/test_gemv.c,
	cblas/test_ger.c, cblas/test_hbmv.c, cblas/test_hemm.c,
	cblas/test_hemv.c, cblas/test_her.c, cblas/test_her2.c,
	cblas/test_her2k.c, cblas/test_herk.c, cblas/test_hpmv.c,
	cblas/test_hpr.c, cblas/test_hpr2.c, cblas/test_nrm2.c,
	cblas/test_rot.c, cblas/test_rotg.c, cblas/test_rotm.c,
	cblas/test_rotmg.c, cblas/test_sbmv.c, cblas/test_scal.c,
	cblas/test_spmv.c, cblas/test_spr.c, cblas/test_spr2.c,
	cblas/test_swap.c, cblas/test_symm.c, cblas/test_symv.c,
	cblas/test_syr.c, cblas/test_syr2.c, cblas/test_syr2k.c,
	cblas/test_syrk.c, cblas/test_tbmv.c, cblas/test_tbsv.c,
	cblas/test_tpmv.c, cblas/test_tpsv.c, cblas/test_trmm.c,
	cblas/test_trmv.c, cblas/test_trsm.c, cblas/test_trsv.c,
	cblas/tests.c, cblas/tests.h, cblas/xerbla.c, cblas/zaxpy.c,
	cblas/zcopy.c, cblas/zdotc_sub.c, cblas/zdotu_sub.c, cblas/zdscal.c,
	cblas/zgbmv.c, cblas/zgemm.c, cblas/zgemv.c, cblas/zgerc.c,
	cblas/zgeru.c, cblas/zhbmv.c, cblas/zhemm.c, cblas/zhemv.c,
	cblas/zher.c, cblas/zher2.c, cblas/zher2k.c, cblas/zherk.c,
	cblas/zhpmv.c, cblas/zhpr.c, cblas/zhpr2.c, cblas/zscal.c,
	cblas/zswap.c, cblas/zsymm.c, cblas/zsyr2k.c, cblas/zsyrk.c,
	cblas/ztbmv.c, cblas/ztbsv.c, cblas/ztpmv.c, cblas/ztpsv.c,
	cblas/ztrmm.c, cblas/ztrmv.c, cblas/ztrsm.c, cblas/ztrsv.c,
	cdf/ChangeLog, cdf/Makefile.am, cdf/Makefile.in, cdf/beta.c,
	cdf/beta_inc.c, cdf/betainv.c, cdf/binomial.c, cdf/cauchy.c,
	cdf/cauchyinv.c, cdf/chisq.c, cdf/chisqinv.c, cdf/error.h,
	cdf/exponential.c, cdf/exponentialinv.c, cdf/exppow.c, cdf/fdist.c,
	cdf/fdistinv.c, cdf/flat.c, cdf/flatinv.c, cdf/gamma.c,
	cdf/gammainv.c, cdf/gauss.c, cdf/gaussinv.c, cdf/geometric.c,
	cdf/gsl_cdf.h, cdf/gumbel1.c, cdf/gumbel1inv.c, cdf/gumbel2.c,
	cdf/gumbel2inv.c, cdf/hypergeometric.c, cdf/laplace.c,
	cdf/laplaceinv.c, cdf/logistic.c, cdf/logisticinv.c, cdf/lognormal.c,
	cdf/lognormalinv.c, cdf/nbinomial.c, cdf/pareto.c, cdf/paretoinv.c,
	cdf/pascal.c, cdf/poisson.c, cdf/rat_eval.h, cdf/rayleigh.c,
	cdf/rayleighinv.c, cdf/tdist.c, cdf/tdistinv.c, cdf/test.c,
	cdf/test_auto.c, cdf/weibull.c, cdf/weibullinv.c, cheb/ChangeLog,
	cheb/Makefile.am, cheb/Makefile.in, cheb/deriv.c, cheb/eval.c,
	cheb/gsl_chebyshev.h, cheb/init.c, cheb/integ.c, cheb/test.c,
	combination/ChangeLog, combination/Makefile.am,
	combination/Makefile.in, combination/combination.c,
	combination/file.c, combination/gsl_combination.h,
	combination/init.c, combination/test.c, complex/ChangeLog,
	complex/Makefile.am, complex/Makefile.in, complex/TODO,
	complex/gsl_complex.h, complex/gsl_complex_math.h, complex/math.c,
	complex/results.h, complex/results1.h, complex/results_real.h,
	complex/test.c, const/ChangeLog, const/Makefile.am,
	const/Makefile.in, const/TODO, const/gsl_const.h,
	const/gsl_const_cgs.h, const/gsl_const_cgsm.h, const/gsl_const_mks.h,
	const/gsl_const_mksa.h, const/gsl_const_num.h, const/test.c,
	deriv/ChangeLog, deriv/Makefile.am, deriv/Makefile.in, deriv/deriv.c,
	deriv/gsl_deriv.h, deriv/test.c, dht/ChangeLog, dht/Makefile.am,
	dht/Makefile.in, dht/dht.c, dht/gsl_dht.h, dht/test.c,
	diff/ChangeLog, diff/Makefile.am, diff/Makefile.in, diff/diff.c,
	diff/gsl_diff.h, diff/test.c, doc/12-cities.eps, doc/ChangeLog,
	doc/Makefile.am, doc/Makefile.in, doc/algorithm.sty,
	doc/algorithmic.sty, doc/autoconf.texi, doc/blas.texi,
	doc/bspline.eps, doc/bspline.texi, doc/calc.sty, doc/cblas.texi,
	doc/cheb.eps, doc/cheb.texi, doc/combination.texi, doc/complex.texi,
	doc/const.texi, doc/debug.texi, doc/dht.texi, doc/diff.texi,
	doc/dwt-orig.eps, doc/dwt-samp.eps, doc/dwt.texi, doc/eigen.texi,
	doc/err.texi, doc/fdl.texi, doc/fft-complex-radix2-f.eps,
	doc/fft-complex-radix2-t.eps, doc/fft-complex-radix2.eps,
	doc/fft-real-mixedradix.eps, doc/fft.texi, doc/fftalgorithms.bib,
	doc/fftalgorithms.tex, doc/final-route.eps, doc/fit-exp.eps,
	doc/fit-wlinear.eps, doc/fit-wlinear2.eps, doc/fitting.texi,
	doc/freemanuals.texi, doc/gpl.texi, doc/gsl-config.1,
	doc/gsl-design.texi, doc/gsl-histogram.1, doc/gsl-randist.1,
	doc/gsl-ref.info, doc/gsl-ref.info-1, doc/gsl-ref.info-2,
	doc/gsl-ref.info-3, doc/gsl-ref.info-4, doc/gsl-ref.info-5,
	doc/gsl-ref.info-6, doc/gsl-ref.texi, doc/gsl.3, doc/histogram.eps,
	doc/histogram.texi, doc/histogram2d.eps, doc/ieee754.texi,
	doc/initial-route.eps, doc/integration.texi, doc/interp.texi,
	doc/interp2.eps, doc/interpp2.eps, doc/intro.texi, doc/landau.dat,
	doc/linalg.texi, doc/math.texi, doc/mdate-sh, doc/min-interval.eps,
	doc/min.texi, doc/montecarlo.texi, doc/multifit.texi,
	doc/multimin.eps, doc/multimin.texi, doc/multiroots.texi,
	doc/ntuple.eps, doc/ntuple.texi, doc/ode-initval.texi,
	doc/permutation.texi, doc/poly.texi, doc/qrng.eps, doc/qrng.texi,
	doc/rand-bernoulli.tex, doc/rand-beta.tex, doc/rand-binomial.tex,
	doc/rand-bivariate-gaussian.tex, doc/rand-cauchy.tex,
	doc/rand-chisq.tex, doc/rand-erlang.tex, doc/rand-exponential.tex,
	doc/rand-exppow.tex, doc/rand-fdist.tex, doc/rand-flat.tex,
	doc/rand-gamma.tex, doc/rand-gaussian-tail.tex,
	doc/rand-gaussian.tex, doc/rand-geometric.tex, doc/rand-gumbel.tex,
	doc/rand-gumbel1.tex, doc/rand-gumbel2.tex,
	doc/rand-hypergeometric.tex, doc/rand-landau.tex,
	doc/rand-laplace.tex, doc/rand-levy.tex, doc/rand-levyskew.tex,
	doc/rand-logarithmic.tex, doc/rand-logistic.tex,
	doc/rand-lognormal.tex, doc/rand-nbinomial.tex, doc/rand-pareto.tex,
	doc/rand-pascal.tex, doc/rand-poisson.tex,
	doc/rand-rayleigh-tail.tex, doc/rand-rayleigh.tex,
	doc/rand-tdist.tex, doc/rand-weibull.tex, doc/randist.texi,
	doc/random-walk.tex, doc/randplots.gnp, doc/rng.texi,
	doc/roots-bisection.eps, doc/roots-false-position.eps,
	doc/roots-newtons-method.eps, doc/roots-secant-method.eps,
	doc/roots.texi, doc/siman-energy.eps, doc/siman-test.eps,
	doc/siman.texi, doc/sort.texi, doc/specfunc-airy.texi,
	doc/specfunc-bessel.texi, doc/specfunc-clausen.texi,
	doc/specfunc-coulomb.texi, doc/specfunc-coupling.texi,
	doc/specfunc-dawson.texi, doc/specfunc-debye.texi,
	doc/specfunc-dilog.texi, doc/specfunc-elementary.texi,
	doc/specfunc-ellint.texi, doc/specfunc-elljac.texi,
	doc/specfunc-erf.texi, doc/specfunc-exp.texi,
	doc/specfunc-expint.texi, doc/specfunc-fermi-dirac.texi,
	doc/specfunc-gamma.texi, doc/specfunc-gegenbauer.texi,
	doc/specfunc-hyperg.texi, doc/specfunc-laguerre.texi,
	doc/specfunc-lambert.texi, doc/specfunc-legendre.texi,
	doc/specfunc-log.texi, doc/specfunc-mathieu.texi,
	doc/specfunc-pow-int.texi, doc/specfunc-psi.texi,
	doc/specfunc-synchrotron.texi, doc/specfunc-transport.texi,
	doc/specfunc-trig.texi, doc/specfunc-zeta.texi, doc/specfunc.texi,
	doc/stamp-vti, doc/statistics.texi, doc/sum.texi, doc/texinfo.tex,
	doc/usage.texi, doc/vdp.eps, doc/vectors.texi, doc/version-ref.texi,
	doc/examples/blas.c, doc/examples/blas.out, doc/examples/block.c,
	doc/examples/block.out, doc/examples/bspline.c, doc/examples/cblas.c,
	doc/examples/cblas.out, doc/examples/cdf.c, doc/examples/cdf.out,
	doc/examples/cheb.c, doc/examples/combination.c,
	doc/examples/combination.out, doc/examples/const.c,
	doc/examples/const.out, doc/examples/demo_fn.c,
	doc/examples/demo_fn.h, doc/examples/diff.c, doc/examples/diff.out,
	doc/examples/dwt.c, doc/examples/dwt.dat, doc/examples/ecg.dat,
	doc/examples/eigen.c, doc/examples/eigen_nonsymm.c,
	doc/examples/expfit.c, doc/examples/fft.c, doc/examples/fftmr.c,
	doc/examples/fftreal.c, doc/examples/fitting.c,
	doc/examples/fitting2.c, doc/examples/fitting3.c,
	doc/examples/histogram.c, doc/examples/histogram2d.c,
	doc/examples/ieee.c, doc/examples/ieeeround.c,
	doc/examples/integration.c, doc/examples/integration.out,
	doc/examples/interp.c, doc/examples/interpp.c, doc/examples/intro.c,
	doc/examples/intro.out, doc/examples/linalglu.c,
	doc/examples/linalglu.out, doc/examples/matrix.c,
	doc/examples/matrixw.c, doc/examples/min.c, doc/examples/min.out,
	doc/examples/monte.c, doc/examples/nlfit.c, doc/examples/ntupler.c,
	doc/examples/ntuplew.c, doc/examples/ode-initval.c,
	doc/examples/odefixed.c, doc/examples/permseq.c,
	doc/examples/permshuffle.c, doc/examples/polyroots.c,
	doc/examples/polyroots.out, doc/examples/qrng.c,
	doc/examples/randpoisson.2.out, doc/examples/randpoisson.c,
	doc/examples/randpoisson.out, doc/examples/randwalk.c,
	doc/examples/rng.c, doc/examples/rng.out, doc/examples/rngunif.2.out,
	doc/examples/rngunif.c, doc/examples/rngunif.out,
	doc/examples/rootnewt.c, doc/examples/roots.c, doc/examples/siman.c,
	doc/examples/sortsmall.c, doc/examples/sortsmall.out,
	doc/examples/specfun.c, doc/examples/specfun.out,
	doc/examples/specfun_e.c, doc/examples/specfun_e.out,
	doc/examples/stat.c, doc/examples/stat.out, doc/examples/statsort.c,
	doc/examples/statsort.out, doc/examples/sum.c, doc/examples/sum.out,
	doc/examples/vector.c, doc/examples/vectorr.c,
	doc/examples/vectorview.c, doc/examples/vectorview.out,
	doc/examples/vectorw.c, eigen/ChangeLog, eigen/Makefile.am,
	eigen/Makefile.in, eigen/TODO, eigen/francis.c, eigen/gsl_eigen.h,
	eigen/herm.c, eigen/hermv.c, eigen/jacobi.c, eigen/nonsymm.c,
	eigen/nonsymmv.c, eigen/qrstep.c, eigen/schur.c, eigen/schur.h,
	eigen/sort.c, eigen/symm.c, eigen/symmv.c, eigen/test.c,
	err/ChangeLog, err/Makefile.am, err/Makefile.in, err/TODO,
	err/error.c, err/gsl_errno.h, err/gsl_message.h, err/message.c,
	err/stream.c, err/strerror.c, err/test.c, fft/ChangeLog,
	fft/Makefile.am, fft/Makefile.in, fft/TODO, fft/bitreverse.c,
	fft/bitreverse.h, fft/c_init.c, fft/c_main.c, fft/c_pass.h,
	fft/c_pass_2.c, fft/c_pass_3.c, fft/c_pass_4.c, fft/c_pass_5.c,
	fft/c_pass_6.c, fft/c_pass_7.c, fft/c_pass_n.c, fft/c_radix2.c,
	fft/compare.h, fft/compare_source.c, fft/complex_internal.h,
	fft/dft.c, fft/dft_source.c, fft/factorize.c, fft/factorize.h,
	fft/fft.c, fft/gsl_dft_complex.h, fft/gsl_dft_complex_float.h,
	fft/gsl_fft.h, fft/gsl_fft_complex.h, fft/gsl_fft_complex_float.h,
	fft/gsl_fft_halfcomplex.h, fft/gsl_fft_halfcomplex_float.h,
	fft/gsl_fft_real.h, fft/gsl_fft_real_float.h, fft/hc_init.c,
	fft/hc_main.c, fft/hc_pass.h, fft/hc_pass_2.c, fft/hc_pass_3.c,
	fft/hc_pass_4.c, fft/hc_pass_5.c, fft/hc_pass_n.c, fft/hc_radix2.c,
	fft/hc_unpack.c, fft/real_init.c, fft/real_main.c, fft/real_pass.h,
	fft/real_pass_2.c, fft/real_pass_3.c, fft/real_pass_4.c,
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	fft/real_unpack.c, fft/signals.c, fft/signals.h,
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	fft/test_real_source.c, fft/test_trap_source.c, fft/urand.c,
	fit/ChangeLog, fit/Makefile.am, fit/Makefile.in, fit/gsl_fit.h,
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	histogram/TODO, histogram/add.c, histogram/add2d.c,
	histogram/calloc_range.c, histogram/calloc_range2d.c,
	histogram/copy.c, histogram/copy2d.c, histogram/file.c,
	histogram/file2d.c, histogram/find.c, histogram/find2d.c,
	histogram/get.c, histogram/get2d.c, histogram/gsl_histogram.h,
	histogram/gsl_histogram2d.h, histogram/init.c, histogram/init2d.c,
	histogram/maxval.c, histogram/maxval2d.c, histogram/oper.c,
	histogram/oper2d.c, histogram/params.c, histogram/params2d.c,
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	histogram/test.c, histogram/test1d.c, histogram/test1d_resample.c,
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	ieee-utils/Makefile.in, ieee-utils/TODO, ieee-utils/endian.c,
	ieee-utils/env.c, ieee-utils/fp-aix.c, ieee-utils/fp-darwin.c,
	ieee-utils/fp-darwin86.c, ieee-utils/fp-freebsd.c,
	ieee-utils/fp-gnuc99.c, ieee-utils/fp-gnum68k.c,
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	ieee-utils/fp-gnux86.c, ieee-utils/fp-hpux.c, ieee-utils/fp-hpux11.c,
	ieee-utils/fp-irix.c, ieee-utils/fp-netbsd.c,
	ieee-utils/fp-openbsd.c, ieee-utils/fp-os2emx.c,
	ieee-utils/fp-solaris.c, ieee-utils/fp-sunos4.c,
	ieee-utils/fp-tru64.c, ieee-utils/fp-unknown.c, ieee-utils/fp.c,
	ieee-utils/gsl_ieee_utils.h, ieee-utils/make_rep.c,
	ieee-utils/print.c, ieee-utils/read.c, ieee-utils/standardize.c,
	ieee-utils/test.c, integration/ChangeLog, integration/Makefile.am,
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	integration/err.c, integration/gsl_integration.h,
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	integration/qmomof.c, integration/qng.c, integration/qng.h,
	integration/qpsrt.c, integration/qpsrt2.c, integration/reset.c,
	integration/set_initial.c, integration/test.c, integration/tests.c,
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	interpolation/ChangeLog, interpolation/Makefile.am,
	interpolation/Makefile.in, interpolation/TODO, interpolation/accel.c,
	interpolation/akima.c, interpolation/bsearch.c,
	interpolation/bsearch.h, interpolation/cspline.c,
	interpolation/gsl_interp.h, interpolation/gsl_spline.h,
	interpolation/integ_eval.h, interpolation/interp.c,
	interpolation/linear.c, interpolation/poly.c, interpolation/spline.c,
	interpolation/test.c, linalg/ChangeLog, linalg/Makefile.am,
	linalg/Makefile.in, linalg/TODO, linalg/apply_givens.c,
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	linalg/cholesky.c, linalg/exponential.c, linalg/givens.c,
	linalg/gsl_linalg.h, linalg/hermtd.c, linalg/hessenberg.c,
	linalg/hh.c, linalg/householder.c, linalg/householdercomplex.c,
	linalg/lq.c, linalg/lu.c, linalg/luc.c, linalg/multiply.c,
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	matrix/file.c, matrix/file_source.c, matrix/getset.c,
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	matrix/gsl_matrix_char.h, matrix/gsl_matrix_complex_double.h,
	matrix/gsl_matrix_complex_float.h,
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	matrix/oper_source.c, matrix/prop.c, matrix/prop_source.c,
	matrix/rowcol.c, matrix/rowcol_source.c, matrix/submatrix.c,
	matrix/submatrix_source.c, matrix/swap.c, matrix/swap_source.c,
	matrix/test.c, matrix/test_complex_source.c, matrix/test_source.c,
	matrix/test_static.c, matrix/view.c, matrix/view.h,
	matrix/view_source.c, min/ChangeLog, min/Makefile.am,
	min/Makefile.in, min/bracketing.c, min/brent.c, min/convergence.c,
	min/fsolver.c, min/golden.c, min/gsl_min.h, min/min.h, min/test.c,
	min/test.h, min/test_funcs.c, monte/ChangeLog, monte/Makefile.am,
	monte/Makefile.in, monte/README, monte/TODO, monte/gsl_monte.h,
	monte/gsl_monte_miser.h, monte/gsl_monte_plain.h,
	monte/gsl_monte_vegas.h, monte/miser.c, monte/plain.c, monte/test.c,
	monte/test_main.c, monte/vegas.c, multifit/ChangeLog,
	multifit/Makefile.am, multifit/Makefile.in, multifit/TODO,
	multifit/convergence.c, multifit/covar.c, multifit/fdfsolver.c,
	multifit/fsolver.c, multifit/gradient.c, multifit/gsl_multifit.h,
	multifit/gsl_multifit_nlin.h, multifit/lmder.c, multifit/lmiterate.c,
	multifit/lmpar.c, multifit/lmset.c, multifit/lmutil.c,
	multifit/multilinear.c, multifit/qrsolv.c, multifit/test.c,
	multifit/test_brown.c, multifit/test_enso.c,
	multifit/test_estimator.c, multifit/test_filip.c, multifit/test_fn.c,
	multifit/test_hahn1.c, multifit/test_kirby2.c,
	multifit/test_longley.c, multifit/test_nelson.c,
	multifit/test_pontius.c, multifit/work.c, multimin/ChangeLog,
	multimin/Makefile.am, multimin/Makefile.in, multimin/TODO,
	multimin/conjugate_fr.c, multimin/conjugate_pr.c,
	multimin/convergence.c, multimin/diff.c,
	multimin/directional_minimize.c, multimin/fdfminimizer.c,
	multimin/fminimizer.c, multimin/gsl_multimin.h,
	multimin/linear_minimize.c, multimin/linear_wrapper.c,
	multimin/simplex.c, multimin/steepest_descent.c, multimin/test.c,
	multimin/test_funcs.c, multimin/test_funcs.h, multimin/vector_bfgs.c,
	multimin/vector_bfgs2.c, multiroots/ChangeLog,
	multiroots/Makefile.am, multiroots/Makefile.in, multiroots/broyden.c,
	multiroots/convergence.c, multiroots/dnewton.c, multiroots/dogleg.c,
	multiroots/enorm.c, multiroots/fdfsolver.c, multiroots/fdjac.c,
	multiroots/fsolver.c, multiroots/gnewton.c,
	multiroots/gsl_multiroots.h, multiroots/hybrid.c,
	multiroots/hybridj.c, multiroots/newton.c, multiroots/test.c,
	multiroots/test_funcs.c, multiroots/test_funcs.h, ntuple/ChangeLog,
	ntuple/Makefile.am, ntuple/Makefile.in, ntuple/gsl_ntuple.h,
	ntuple/ntuple.c, ntuple/test.c, ode-initval/ChangeLog,
	ode-initval/Makefile.am, ode-initval/Makefile.in, ode-initval/TODO,
	ode-initval/bsimp.c, ode-initval/control.c, ode-initval/cscal.c,
	ode-initval/cstd.c, ode-initval/evolve.c, ode-initval/gear1.c,
	ode-initval/gear2.c, ode-initval/gsl_odeiv.h,
	ode-initval/odeiv_util.h, ode-initval/rk2.c, ode-initval/rk2imp.c,
	ode-initval/rk2simp.c, ode-initval/rk4.c, ode-initval/rk4imp.c,
	ode-initval/rk8pd.c, ode-initval/rkck.c, ode-initval/rkf45.c,
	ode-initval/step.c, ode-initval/test.c, permutation/ChangeLog,
	permutation/Makefile.am, permutation/Makefile.in,
	permutation/canonical.c, permutation/file.c,
	permutation/gsl_permutation.h, permutation/gsl_permute.h,
	permutation/gsl_permute_char.h,
	permutation/gsl_permute_complex_double.h,
	permutation/gsl_permute_complex_float.h,
	permutation/gsl_permute_complex_long_double.h,
	permutation/gsl_permute_double.h, permutation/gsl_permute_float.h,
	permutation/gsl_permute_int.h, permutation/gsl_permute_long.h,
	permutation/gsl_permute_long_double.h,
	permutation/gsl_permute_short.h, permutation/gsl_permute_uchar.h,
	permutation/gsl_permute_uint.h, permutation/gsl_permute_ulong.h,
	permutation/gsl_permute_ushort.h, permutation/gsl_permute_vector.h,
	permutation/gsl_permute_vector_char.h,
	permutation/gsl_permute_vector_complex_double.h,
	permutation/gsl_permute_vector_complex_float.h,
	permutation/gsl_permute_vector_complex_long_double.h,
	permutation/gsl_permute_vector_double.h,
	permutation/gsl_permute_vector_float.h,
	permutation/gsl_permute_vector_int.h,
	permutation/gsl_permute_vector_long.h,
	permutation/gsl_permute_vector_long_double.h,
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	permutation/gsl_permute_vector_uint.h,
	permutation/gsl_permute_vector_ulong.h,
	permutation/gsl_permute_vector_ushort.h, permutation/init.c,
	permutation/permutation.c, permutation/permute.c,
	permutation/permute_source.c, permutation/test.c, poly/ChangeLog,
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	poly/companion.c, poly/dd.c, poly/eval.c, poly/gsl_poly.h, poly/qr.c,
	poly/solve_cubic.c, poly/solve_quadratic.c, poly/test.c,
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	qrng/qrng.c, qrng/sobol.c, qrng/test.c, randist/ChangeLog,
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	randist/bernoulli.c, randist/beta.c, randist/bigauss.c,
	randist/binomial.c, randist/binomial_tpe.c, randist/cauchy.c,
	randist/chisq.c, randist/dirichlet.c, randist/discrete.c,
	randist/erlang.c, randist/exponential.c, randist/exppow.c,
	randist/fdist.c, randist/flat.c, randist/gamma.c, randist/gauss.c,
	randist/gausstail.c, randist/gausszig.c, randist/geometric.c,
	randist/gsl_randist.h, randist/gumbel.c, randist/hyperg.c,
	randist/landau.c, randist/laplace.c, randist/levy.c,
	randist/logarithmic.c, randist/logistic.c, randist/lognormal.c,
	randist/multinomial.c, randist/nbinomial.c, randist/pareto.c,
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	rng/file.c, rng/fishman18.c, rng/fishman20.c, rng/fishman2x.c,
	rng/gfsr4.c, rng/gsl_rng.h, rng/knuthran.c, rng/knuthran2.c,
	rng/knuthran2002.c, rng/lecuyer21.c, rng/minstd.c, rng/mrg.c,
	rng/mt.c, rng/r250.c, rng/ran0.c, rng/ran1.c, rng/ran2.c, rng/ran3.c,
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	rng/ranlux.c, rng/ranlxd.c, rng/ranlxs.c, rng/ranmar.c, rng/rng.c,
	rng/schrage.c, rng/slatec.c, rng/taus.c, rng/taus113.c, rng/test.c,
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	roots/brent.c, roots/convergence.c, roots/falsepos.c,
	roots/fdfsolver.c, roots/fsolver.c, roots/gsl_roots.h,
	roots/newton.c, roots/roots.h, roots/secant.c, roots/steffenson.c,
	roots/test.c, roots/test.h, roots/test_funcs.c, siman/ChangeLog,
	siman/Makefile.am, siman/Makefile.in, siman/TODO, siman/gsl_siman.h,
	siman/siman.c, siman/siman_test_driver.sh, siman/siman_tsp.c,
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	sort/gsl_sort_uchar.h, sort/gsl_sort_uint.h, sort/gsl_sort_ulong.h,
	sort/gsl_sort_ushort.h, sort/gsl_sort_vector.h,
	sort/gsl_sort_vector_char.h, sort/gsl_sort_vector_double.h,
	sort/gsl_sort_vector_float.h, sort/gsl_sort_vector_int.h,
	sort/gsl_sort_vector_long.h, sort/gsl_sort_vector_long_double.h,
	sort/gsl_sort_vector_short.h, sort/gsl_sort_vector_uchar.h,
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	sort/sortvec.c, sort/sortvec_source.c, sort/sortvecind.c,
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	sort/subsetind.c, sort/subsetind_source.c, sort/test.c,
	sort/test_heapsort.c, sort/test_source.c, specfunc/ChangeLog,
	specfunc/Makefile.am, specfunc/Makefile.in, specfunc/TODO,
	specfunc/airy.c, specfunc/airy_der.c, specfunc/airy_zero.c,
	specfunc/atanint.c, specfunc/bessel.c, specfunc/bessel.h,
	specfunc/bessel_I0.c, specfunc/bessel_I1.c, specfunc/bessel_In.c,
	specfunc/bessel_Inu.c, specfunc/bessel_J0.c, specfunc/bessel_J1.c,
	specfunc/bessel_Jn.c, specfunc/bessel_Jnu.c, specfunc/bessel_K0.c,
	specfunc/bessel_K1.c, specfunc/bessel_Kn.c, specfunc/bessel_Knu.c,
	specfunc/bessel_Y0.c, specfunc/bessel_Y1.c, specfunc/bessel_Yn.c,
	specfunc/bessel_Ynu.c, specfunc/bessel_amp_phase.c,
	specfunc/bessel_amp_phase.h, specfunc/bessel_i.c,
	specfunc/bessel_j.c, specfunc/bessel_k.c, specfunc/bessel_olver.c,
	specfunc/bessel_olver.h, specfunc/bessel_sequence.c,
	specfunc/bessel_temme.c, specfunc/bessel_temme.h,
	specfunc/bessel_y.c, specfunc/bessel_zero.c, specfunc/beta.c,
	specfunc/beta_inc.c, specfunc/cheb_eval.c, specfunc/cheb_eval_mode.c,
	specfunc/chebyshev.h, specfunc/check.h, specfunc/clausen.c,
	specfunc/coulomb.c, specfunc/coulomb_bound.c, specfunc/coupling.c,
	specfunc/dawson.c, specfunc/debye.c, specfunc/dilog.c,
	specfunc/elementary.c, specfunc/ellint.c, specfunc/elljac.c,
	specfunc/erfc.c, specfunc/error.h, specfunc/eval.h, specfunc/exp.c,
	specfunc/expint.c, specfunc/expint3.c, specfunc/fermi_dirac.c,
	specfunc/gamma.c, specfunc/gamma_inc.c, specfunc/gegenbauer.c,
	specfunc/gsl_sf.h, specfunc/gsl_sf_airy.h, specfunc/gsl_sf_bessel.h,
	specfunc/gsl_sf_clausen.h, specfunc/gsl_sf_coulomb.h,
	specfunc/gsl_sf_coupling.h, specfunc/gsl_sf_dawson.h,
	specfunc/gsl_sf_debye.h, specfunc/gsl_sf_dilog.h,
	specfunc/gsl_sf_elementary.h, specfunc/gsl_sf_ellint.h,
	specfunc/gsl_sf_elljac.h, specfunc/gsl_sf_erf.h,
	specfunc/gsl_sf_exp.h, specfunc/gsl_sf_expint.h,
	specfunc/gsl_sf_fermi_dirac.h, specfunc/gsl_sf_gamma.h,
	specfunc/gsl_sf_gegenbauer.h, specfunc/gsl_sf_hyperg.h,
	specfunc/gsl_sf_laguerre.h, specfunc/gsl_sf_lambert.h,
	specfunc/gsl_sf_legendre.h, specfunc/gsl_sf_log.h,
	specfunc/gsl_sf_mathieu.h, specfunc/gsl_sf_pow_int.h,
	specfunc/gsl_sf_psi.h, specfunc/gsl_sf_result.h,
	specfunc/gsl_sf_synchrotron.h, specfunc/gsl_sf_transport.h,
	specfunc/gsl_sf_trig.h, specfunc/gsl_sf_zeta.h,
	specfunc/gsl_specfunc.h, specfunc/hyperg.c, specfunc/hyperg.h,
	specfunc/hyperg_0F1.c, specfunc/hyperg_1F1.c, specfunc/hyperg_2F0.c,
	specfunc/hyperg_2F1.c, specfunc/hyperg_U.c, specfunc/laguerre.c,
	specfunc/lambert.c, specfunc/legendre.h, specfunc/legendre_H3d.c,
	specfunc/legendre_Qn.c, specfunc/legendre_con.c,
	specfunc/legendre_poly.c, specfunc/log.c, specfunc/mathieu_angfunc.c,
	specfunc/mathieu_charv.c, specfunc/mathieu_coeff.c,
	specfunc/mathieu_radfunc.c, specfunc/mathieu_workspace.c,
	specfunc/poch.c, specfunc/pow_int.c, specfunc/psi.c,
	specfunc/recurse.h, specfunc/result.c, specfunc/shint.c,
	specfunc/sinint.c, specfunc/synchrotron.c, specfunc/test_airy.c,
	specfunc/test_bessel.c, specfunc/test_coulomb.c,
	specfunc/test_dilog.c, specfunc/test_gamma.c, specfunc/test_hyperg.c,
	specfunc/test_legendre.c, specfunc/test_mathieu.c,
	specfunc/test_sf.c, specfunc/test_sf.h, specfunc/transport.c,
	specfunc/trig.c, specfunc/zeta.c, statistics/ChangeLog,
	statistics/Makefile.am, statistics/Makefile.in, statistics/TODO,
	statistics/absdev.c, statistics/absdev_source.c,
	statistics/covariance.c, statistics/covariance_source.c,
	statistics/gsl_statistics.h, statistics/gsl_statistics_char.h,
	statistics/gsl_statistics_double.h,
	statistics/gsl_statistics_float.h, statistics/gsl_statistics_int.h,
	statistics/gsl_statistics_long.h,
	statistics/gsl_statistics_long_double.h,
	statistics/gsl_statistics_short.h, statistics/gsl_statistics_uchar.h,
	statistics/gsl_statistics_uint.h, statistics/gsl_statistics_ulong.h,
	statistics/gsl_statistics_ushort.h, statistics/kurtosis.c,
	statistics/kurtosis_source.c, statistics/lag1.c,
	statistics/lag1_source.c, statistics/mean.c,
	statistics/mean_source.c, statistics/median.c,
	statistics/median_source.c, statistics/minmax.c,
	statistics/minmax_source.c, statistics/p_variance.c,
	statistics/p_variance_source.c, statistics/quantiles.c,
	statistics/quantiles_source.c, statistics/skew.c,
	statistics/skew_source.c, statistics/test.c,
	statistics/test_float_source.c, statistics/test_int_source.c,
	statistics/test_nist.c, statistics/ttest.c,
	statistics/ttest_source.c, statistics/variance.c,
	statistics/variance_source.c, statistics/wabsdev.c,
	statistics/wabsdev_source.c, statistics/wkurtosis.c,
	statistics/wkurtosis_source.c, statistics/wmean.c,
	statistics/wmean_source.c, statistics/wskew.c,
	statistics/wskew_source.c, statistics/wvariance.c,
	statistics/wvariance_source.c, sum/ChangeLog, sum/Makefile.am,
	sum/Makefile.in, sum/gsl_sum.h, sum/levin_u.c, sum/levin_utrunc.c,
	sum/test.c, sum/work_u.c, sum/work_utrunc.c, sys/ChangeLog,
	sys/Makefile.am, sys/Makefile.in, sys/coerce.c, sys/expm1.c,
	sys/fcmp.c, sys/fdiv.c, sys/gsl_sys.h, sys/hypot.c, sys/infnan.c,
	sys/invhyp.c, sys/ldfrexp.c, sys/log1p.c, sys/minmax.c,
	sys/pow_int.c, sys/prec.c, sys/test.c, test/ChangeLog,
	test/Makefile.am, test/Makefile.in, test/gsl_test.h, test/results.c,
	utils/Makefile.am, utils/Makefile.in, utils/README, utils/memcpy.c,
	utils/memmove.c, utils/placeholder.c, utils/strdup.c, utils/strtol.c,
	utils/strtoul.c, utils/system.h, vector/ChangeLog,
	vector/Makefile.am, vector/Makefile.in, vector/TODO, vector/copy.c,
	vector/copy_source.c, vector/file.c, vector/file_source.c,
	vector/gsl_vector.h, vector/gsl_vector_char.h,
	vector/gsl_vector_complex.h, vector/gsl_vector_complex_double.h,
	vector/gsl_vector_complex_float.h,
	vector/gsl_vector_complex_long_double.h, vector/gsl_vector_double.h,
	vector/gsl_vector_float.h, vector/gsl_vector_int.h,
	vector/gsl_vector_long.h, vector/gsl_vector_long_double.h,
	vector/gsl_vector_short.h, vector/gsl_vector_uchar.h,
	vector/gsl_vector_uint.h, vector/gsl_vector_ulong.h,
	vector/gsl_vector_ushort.h, vector/init.c, vector/init_source.c,
	vector/minmax.c, vector/minmax_source.c, vector/oper.c,
	vector/oper_source.c, vector/prop.c, vector/prop_source.c,
	vector/reim.c, vector/reim_source.c, vector/subvector.c,
	vector/subvector_source.c, vector/swap.c, vector/swap_source.c,
	vector/test.c, vector/test_complex_source.c, vector/test_source.c,
	vector/test_static.c, vector/vector.c, vector/vector_source.c,
	vector/view.c, vector/view.h, vector/view_source.c,
	wavelet/ChangeLog, wavelet/Makefile.am, wavelet/Makefile.in,
	wavelet/TODO, wavelet/bspline.c, wavelet/daubechies.c, wavelet/dwt.c,
	wavelet/gsl_wavelet.h, wavelet/gsl_wavelet2d.h, wavelet/haar.c,
	wavelet/test.c, wavelet/wavelet.c: New files.

1 files changed, 718 insertions, 0 deletions

diff --git a/gsl-1.9/doc/montecarlo.texi b/gsl-1.9/doc/montecarlo.texi
new file mode 100644
index 0000000..0c3aabe
--- /dev/null
+++ b/gsl-1.9/doc/montecarlo.texi
@@ -0,0 +1,718 @@
+@cindex Monte Carlo integration
+@cindex stratified sampling in monte carlo integration
+This chapter describes routines for multidimensional Monte Carlo
+integration.  These include the traditional Monte Carlo method and
+adaptive algorithms such as @sc{vegas} and @sc{miser} which use
+importance sampling and stratified sampling techniques. Each algorithm
+computes an estimate of a multidimensional definite integral of the
+form,
+@tex
+\beforedisplay
+$$
+I = \int_{x_l}^{x_u} dx\,\int_{y_l}^{y_u}dy\,... f(x,y,...)
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+I = \int_xl^xu dx \int_yl^yu  dy ...  f(x, y, ...)
+@end example
+
+@end ifinfo
+@noindent
+over a hypercubic region @math{((x_l,x_u)}, @math{(y_l,y_u), ...)} using
+a fixed number of function calls.  The routines also provide a
+statistical estimate of the error on the result.  This error estimate
+should be taken as a guide rather than as a strict error bound---random 
+sampling of the region may not uncover all the important features
+of the function, resulting in an underestimate of the error.
+
+The functions are defined in separate header files for each routine,
+@code{gsl_monte_plain.h}, @file{gsl_monte_miser.h} and
+@file{gsl_monte_vegas.h}.
+
+@menu
+* Monte Carlo Interface::       
+* PLAIN Monte Carlo::  
+* MISER::                       
+* VEGAS::                       
+* Monte Carlo Examples::        
+* Monte Carlo Integration References and Further Reading::  
+@end menu
+
+@node Monte Carlo Interface
+@section Interface
+All of the Monte Carlo integration routines use the same general form of
+interface.  There is an allocator to allocate memory for control
+variables and workspace, a routine to initialize those control
+variables, the integrator itself, and a function to free the space when
+done.
+
+Each integration function requires a random number generator to be
+supplied, and returns an estimate of the integral and its standard
+deviation.  The accuracy of the result is determined by the number of
+function calls specified by the user.  If a known level of accuracy is
+required this can be achieved by calling the integrator several times
+and averaging the individual results until the desired accuracy is
+obtained.  
+
+Random sample points used within the Monte Carlo routines are always
+chosen strictly within the integration region, so that endpoint
+singularities are automatically avoided.
+
+The function to be integrated has its own datatype, defined in the
+header file @file{gsl_monte.h}.
+
+@deftp {Data Type} gsl_monte_function 
+
+This data type defines a general function with parameters for Monte
+Carlo integration.
+
+@table @code
+@item double (* f) (double * @var{x}, size_t @var{dim}, void * @var{params})
+this function should return the value
+@c{$f(x,\hbox{\it params})$}
+@math{f(x,params)} for the argument @var{x} and parameters @var{params},
+where @var{x} is an array of size @var{dim} giving the coordinates of
+the point where the function is to be evaluated.
+
+@item size_t dim
+the number of dimensions for @var{x}.
+
+@item void * params
+a pointer to the parameters of the function.
+@end table
+@end deftp
+
+@noindent
+Here is an example for a quadratic function in two dimensions,
+@tex
+\beforedisplay
+$$
+f(x,y) = a x^2 + b x y + c y^2
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+f(x,y) = a x^2 + b x y + c y^2
+@end example
+
+@end ifinfo
+@noindent
+with @math{a = 3}, @math{b = 2}, @math{c = 1}.  The following code
+defines a @code{gsl_monte_function} @code{F} which you could pass to an
+integrator:
+
+@example
+struct my_f_params @{ double a; double b; double c; @};
+
+double
+my_f (double x[], size_t dim, void * p) @{
+   struct my_f_params * fp = (struct my_f_params *)p;
+
+   if (dim != 2)
+      @{
+        fprintf (stderr, "error: dim != 2");
+        abort ();
+      @}
+
+   return  fp->a * x[0] * x[0] 
+             + fp->b * x[0] * x[1] 
+               + fp->c * x[1] * x[1];
+@}
+
+gsl_monte_function F;
+struct my_f_params params = @{ 3.0, 2.0, 1.0 @};
+
+F.f = &my_f;
+F.dim = 2;
+F.params = &params;
+@end example
+
+@noindent
+The function @math{f(x)} can be evaluated using the following macro,
+
+@example
+#define GSL_MONTE_FN_EVAL(F,x) 
+    (*((F)->f))(x,(F)->dim,(F)->params)
+@end example
+
+@node PLAIN Monte Carlo
+@section PLAIN Monte Carlo
+@cindex plain monte carlo
+The plain Monte Carlo algorithm samples points randomly from the
+integration region to estimate the integral and its error.  Using this
+algorithm the estimate of the integral @math{E(f; N)} for @math{N}
+randomly distributed points @math{x_i} is given by,
+@tex
+\beforedisplay
+$$
+E(f; N) =  V \langle f \rangle = {V \over N} \sum_i^N f(x_i)
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+E(f; N) = =  V <f> = (V / N) \sum_i^N f(x_i)
+@end example
+
+@end ifinfo
+@noindent
+where @math{V} is the volume of the integration region.  The error on
+this estimate @math{\sigma(E;N)} is calculated from the estimated
+variance of the mean,
+@tex
+\beforedisplay
+$$
+\sigma^2 (E; N) = {V \over N } \sum_i^N (f(x_i) - \langle f \rangle)^2.
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+\sigma^2 (E; N) = (V / N) \sum_i^N (f(x_i) -  <f>)^2.
+@end example
+
+@end ifinfo
+@noindent
+For large @math{N} this variance decreases asymptotically as
+@math{\Var(f)/N}, where @math{\Var(f)} is the true variance of the
+function over the integration region.  The error estimate itself should
+decrease as @c{$\sigma(f)/\sqrt{N}$}
+@math{\sigma(f)/\sqrt@{N@}}.  The familiar law of errors
+decreasing as @c{$1/\sqrt{N}$}
+@math{1/\sqrt@{N@}} applies---to reduce the error by a
+factor of 10 requires a 100-fold increase in the number of sample
+points.
+
+The functions described in this section are declared in the header file
+@file{gsl_monte_plain.h}.
+
+@deftypefun {gsl_monte_plain_state *} gsl_monte_plain_alloc (size_t @var{dim})
+This function allocates and initializes a workspace for Monte Carlo
+integration in @var{dim} dimensions.  
+@end deftypefun
+
+@deftypefun int gsl_monte_plain_init (gsl_monte_plain_state* @var{s})
+This function initializes a previously allocated integration state.
+This allows an existing workspace to be reused for different
+integrations.
+@end deftypefun
+
+@deftypefun int gsl_monte_plain_integrate (gsl_monte_function * @var{f}, double * @var{xl}, double * @var{xu}, size_t @var{dim}, size_t @var{calls}, gsl_rng * @var{r}, gsl_monte_plain_state * @var{s}, double * @var{result}, double * @var{abserr})
+This routines uses the plain Monte Carlo algorithm to integrate the
+function @var{f} over the @var{dim}-dimensional hypercubic region
+defined by the lower and upper limits in the arrays @var{xl} and
+@var{xu}, each of size @var{dim}.  The integration uses a fixed number
+of function calls @var{calls}, and obtains random sampling points using
+the random number generator @var{r}. A previously allocated workspace
+@var{s} must be supplied.  The result of the integration is returned in
+@var{result}, with an estimated absolute error @var{abserr}.
+@end deftypefun
+
+@deftypefun void gsl_monte_plain_free (gsl_monte_plain_state * @var{s})
+This function frees the memory associated with the integrator state
+@var{s}.
+@end deftypefun
+
+@node MISER
+@section MISER
+@cindex MISER monte carlo integration
+@cindex recursive stratified sampling, MISER
+
+The @sc{miser} algorithm of Press and Farrar is based on recursive
+stratified sampling.  This technique aims to reduce the overall
+integration error by concentrating integration points in the regions of
+highest variance.
+
+The idea of stratified sampling begins with the observation that for two
+disjoint regions @math{a} and @math{b} with Monte Carlo estimates of the
+integral @math{E_a(f)} and @math{E_b(f)} and variances
+@math{\sigma_a^2(f)} and @math{\sigma_b^2(f)}, the variance
+@math{\Var(f)} of the combined estimate 
+@c{$E(f) = {1\over 2} (E_a(f) + E_b(f))$} 
+@math{E(f) = (1/2) (E_a(f) + E_b(f))} 
+is given by,
+@tex
+\beforedisplay
+$$
+\Var(f) = {\sigma_a^2(f) \over 4 N_a} + {\sigma_b^2(f) \over 4 N_b}.
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+\Var(f) = (\sigma_a^2(f) / 4 N_a) + (\sigma_b^2(f) / 4 N_b).
+@end example
+
+@end ifinfo
+@noindent
+It can be shown that this variance is minimized by distributing the
+points such that,
+@tex
+\beforedisplay
+$$
+{N_a \over N_a+N_b} = {\sigma_a \over \sigma_a + \sigma_b}.
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+N_a / (N_a + N_b) = \sigma_a / (\sigma_a + \sigma_b).
+@end example
+
+@end ifinfo
+@noindent
+Hence the smallest error estimate is obtained by allocating sample
+points in proportion to the standard deviation of the function in each
+sub-region.
+
+The @sc{miser} algorithm proceeds by bisecting the integration region
+along one coordinate axis to give two sub-regions at each step.  The
+direction is chosen by examining all @math{d} possible bisections and
+selecting the one which will minimize the combined variance of the two
+sub-regions.  The variance in the sub-regions is estimated by sampling
+with a fraction of the total number of points available to the current
+step.  The same procedure is then repeated recursively for each of the
+two half-spaces from the best bisection. The remaining sample points are
+allocated to the sub-regions using the formula for @math{N_a} and
+@math{N_b}.  This recursive allocation of integration points continues
+down to a user-specified depth where each sub-region is integrated using
+a plain Monte Carlo estimate.  These individual values and their error
+estimates are then combined upwards to give an overall result and an
+estimate of its error.
+
+The functions described in this section are declared in the header file
+@file{gsl_monte_miser.h}.
+
+@deftypefun {gsl_monte_miser_state *} gsl_monte_miser_alloc (size_t @var{dim})
+This function allocates and initializes a workspace for Monte Carlo
+integration in @var{dim} dimensions.  The workspace is used to maintain
+the state of the integration.
+@end deftypefun
+
+@deftypefun int gsl_monte_miser_init (gsl_monte_miser_state* @var{s})
+This function initializes a previously allocated integration state.
+This allows an existing workspace to be reused for different
+integrations.
+@end deftypefun
+
+@deftypefun int gsl_monte_miser_integrate (gsl_monte_function * @var{f}, double * @var{xl}, double * @var{xu}, size_t @var{dim}, size_t @var{calls}, gsl_rng * @var{r}, gsl_monte_miser_state * @var{s}, double * @var{result}, double * @var{abserr})
+This routines uses the @sc{miser} Monte Carlo algorithm to integrate the
+function @var{f} over the @var{dim}-dimensional hypercubic region
+defined by the lower and upper limits in the arrays @var{xl} and
+@var{xu}, each of size @var{dim}.  The integration uses a fixed number
+of function calls @var{calls}, and obtains random sampling points using
+the random number generator @var{r}. A previously allocated workspace
+@var{s} must be supplied.  The result of the integration is returned in
+@var{result}, with an estimated absolute error @var{abserr}.
+@end deftypefun
+
+@deftypefun void gsl_monte_miser_free (gsl_monte_miser_state * @var{s}) 
+This function frees the memory associated with the integrator state
+@var{s}.
+@end deftypefun
+
+The @sc{miser} algorithm has several configurable parameters. The
+following variables can be accessed through the
+@code{gsl_monte_miser_state} struct,
+
+@deftypevar double estimate_frac
+This parameter specifies the fraction of the currently available number of
+function calls which are allocated to estimating the variance at each
+recursive step. The default value is 0.1.
+@end deftypevar
+
+@deftypevar size_t min_calls
+This parameter specifies the minimum number of function calls required
+for each estimate of the variance. If the number of function calls
+allocated to the estimate using @var{estimate_frac} falls below
+@var{min_calls} then @var{min_calls} are used instead.  This ensures
+that each estimate maintains a reasonable level of accuracy.  The
+default value of @var{min_calls} is @code{16 * dim}.
+@end deftypevar
+
+@deftypevar size_t min_calls_per_bisection
+This parameter specifies the minimum number of function calls required
+to proceed with a bisection step.  When a recursive step has fewer calls
+available than @var{min_calls_per_bisection} it performs a plain Monte
+Carlo estimate of the current sub-region and terminates its branch of
+the recursion.  The default value of this parameter is @code{32 *
+min_calls}.
+@end deftypevar
+
+@deftypevar double alpha
+This parameter controls how the estimated variances for the two
+sub-regions of a bisection are combined when allocating points.  With
+recursive sampling the overall variance should scale better than
+@math{1/N}, since the values from the sub-regions will be obtained using
+a procedure which explicitly minimizes their variance.  To accommodate
+this behavior the @sc{miser} algorithm allows the total variance to
+depend on a scaling parameter @math{\alpha},
+@tex
+\beforedisplay
+$$
+\Var(f) = {\sigma_a \over N_a^\alpha} + {\sigma_b \over N_b^\alpha}.
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+\Var(f) = @{\sigma_a \over N_a^\alpha@} + @{\sigma_b \over N_b^\alpha@}.
+@end example
+
+@end ifinfo
+@noindent
+The authors of the original paper describing @sc{miser} recommend the
+value @math{\alpha = 2} as a good choice, obtained from numerical
+experiments, and this is used as the default value in this
+implementation.
+@end deftypevar
+
+@deftypevar double dither
+This parameter introduces a random fractional variation of size
+@var{dither} into each bisection, which can be used to break the
+symmetry of integrands which are concentrated near the exact center of
+the hypercubic integration region.  The default value of dither is zero,
+so no variation is introduced. If needed, a typical value of
+@var{dither} is 0.1.
+@end deftypevar
+
+@node VEGAS
+@section VEGAS
+@cindex VEGAS monte carlo integration
+@cindex importance sampling, VEGAS
+
+The @sc{vegas} algorithm of Lepage is based on importance sampling.  It
+samples points from the probability distribution described by the
+function @math{|f|}, so that the points are concentrated in the regions
+that make the largest contribution to the integral.
+
+In general, if the Monte Carlo integral of @math{f} is sampled with
+points distributed according to a probability distribution described by
+the function @math{g}, we obtain an estimate @math{E_g(f; N)},
+@tex
+\beforedisplay
+$$
+E_g(f; N) = E(f/g; N)
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+E_g(f; N) = E(f/g; N)
+@end example
+
+@end ifinfo
+@noindent
+with a corresponding variance,
+@tex
+\beforedisplay
+$$
+\Var_g(f; N) = \Var(f/g; N).
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+\Var_g(f; N) = \Var(f/g; N).
+@end example
+
+@end ifinfo
+@noindent
+If the probability distribution is chosen as @math{g = |f|/I(|f|)} then
+it can be shown that the variance @math{V_g(f; N)} vanishes, and the
+error in the estimate will be zero.  In practice it is not possible to
+sample from the exact distribution @math{g} for an arbitrary function, so
+importance sampling algorithms aim to produce efficient approximations
+to the desired distribution.
+
+The @sc{vegas} algorithm approximates the exact distribution by making a
+number of passes over the integration region while histogramming the
+function @math{f}. Each histogram is used to define a sampling
+distribution for the next pass.  Asymptotically this procedure converges
+to the desired distribution. In order
+to avoid the number of histogram bins growing like @math{K^d} the
+probability distribution is approximated by a separable function:
+@c{$g(x_1, x_2,\ldots) = g_1(x_1) g_2(x_2)\ldots$} 
+@math{g(x_1, x_2, ...) = g_1(x_1) g_2(x_2) ...}  
+so that the number of bins required is only @math{Kd}.     
+This is equivalent to locating the peaks of the function from the
+projections of the integrand onto the coordinate axes.  The efficiency
+of @sc{vegas} depends on the validity of this assumption.  It is most
+efficient when the peaks of the integrand are well-localized.  If an
+integrand can be rewritten in a form which is approximately separable
+this will increase the efficiency of integration with @sc{vegas}.
+
+@sc{vegas} incorporates a number of additional features, and combines both
+stratified sampling and importance sampling.  The integration region is
+divided into a number of ``boxes'', with each box getting a fixed
+number of points (the goal is 2).  Each box can then have a fractional
+number of bins, but if the ratio of bins-per-box is less than two, Vegas switches to a
+kind variance reduction (rather than importance sampling).
+
+
+@deftypefun {gsl_monte_vegas_state *} gsl_monte_vegas_alloc (size_t @var{dim})
+This function allocates and initializes a workspace for Monte Carlo
+integration in @var{dim} dimensions.  The workspace is used to maintain
+the state of the integration.
+@end deftypefun
+
+@deftypefun int gsl_monte_vegas_init (gsl_monte_vegas_state* @var{s})
+This function initializes a previously allocated integration state.
+This allows an existing workspace to be reused for different
+integrations.
+@end deftypefun
+
+@deftypefun int gsl_monte_vegas_integrate (gsl_monte_function * @var{f}, double * @var{xl}, double * @var{xu}, size_t @var{dim}, size_t @var{calls}, gsl_rng * @var{r}, gsl_monte_vegas_state * @var{s}, double * @var{result}, double * @var{abserr})
+This routines uses the @sc{vegas} Monte Carlo algorithm to integrate the
+function @var{f} over the @var{dim}-dimensional hypercubic region
+defined by the lower and upper limits in the arrays @var{xl} and
+@var{xu}, each of size @var{dim}.  The integration uses a fixed number
+of function calls @var{calls}, and obtains random sampling points using
+the random number generator @var{r}. A previously allocated workspace
+@var{s} must be supplied.  The result of the integration is returned in
+@var{result}, with an estimated absolute error @var{abserr}.  The result
+and its error estimate are based on a weighted average of independent
+samples. The chi-squared per degree of freedom for the weighted average
+is returned via the state struct component, @var{s->chisq}, and must be
+consistent with 1 for the weighted average to be reliable.
+@end deftypefun
+
+@deftypefun void gsl_monte_vegas_free (gsl_monte_vegas_state * @var{s})
+This function frees the memory associated with the integrator state
+@var{s}.
+@end deftypefun
+
+The @sc{vegas} algorithm computes a number of independent estimates of the
+integral internally, according to the @code{iterations} parameter
+described below, and returns their weighted average.  Random sampling of
+the integrand can occasionally produce an estimate where the error is
+zero, particularly if the function is constant in some regions. An
+estimate with zero error causes the weighted average to break down and
+must be handled separately. In the original Fortran implementations of
+@sc{vegas} the error estimate is made non-zero by substituting a small
+value (typically @code{1e-30}).  The implementation in GSL differs from
+this and avoids the use of an arbitrary constant---it either assigns
+the value a weight which is the average weight of the preceding
+estimates or discards it according to the following procedure,
+
+@table @asis
+@item current estimate has zero error, weighted average has finite error
+
+The current estimate is assigned a weight which is the average weight of
+the preceding estimates.
+
+@item current estimate has finite error, previous estimates had zero error
+
+The previous estimates are discarded and the weighted averaging
+procedure begins with the current estimate.
+
+@item current estimate has zero error, previous estimates had zero error
+
+The estimates are averaged using the arithmetic mean, but no error is computed.
+@end table
+
+The @sc{vegas} algorithm is highly configurable. The following variables
+can be accessed through the @code{gsl_monte_vegas_state} struct,
+
+@deftypevar double result
+@deftypevarx double sigma
+These parameters contain the raw value of the integral @var{result} and
+its error @var{sigma} from the last iteration of the algorithm.
+@end deftypevar
+
+@deftypevar double chisq
+This parameter gives the chi-squared per degree of freedom for the
+weighted estimate of the integral.  The value of @var{chisq} should be
+close to 1.  A value of @var{chisq} which differs significantly from 1
+indicates that the values from different iterations are inconsistent.
+In this case the weighted error will be under-estimated, and further
+iterations of the algorithm are needed to obtain reliable results.
+@end deftypevar
+
+@deftypevar double alpha
+The parameter @code{alpha} controls the stiffness of the rebinning
+algorithm.  It is typically set between one and two. A value of zero
+prevents rebinning of the grid.  The default value is 1.5.
+@end deftypevar
+
+@deftypevar size_t iterations
+The number of iterations to perform for each call to the routine. The
+default value is 5 iterations.
+@end deftypevar
+
+@deftypevar int stage
+Setting this determines the @dfn{stage} of the calculation.  Normally,
+@code{stage = 0} which begins with a new uniform grid and empty weighted
+average.  Calling vegas with @code{stage = 1} retains the grid from the
+previous run but discards the weighted average, so that one can ``tune''
+the grid using a relatively small number of points and then do a large
+run with @code{stage = 1} on the optimized grid.  Setting @code{stage =
+2} keeps the grid and the weighted average from the previous run, but
+may increase (or decrease) the number of histogram bins in the grid
+depending on the number of calls available.  Choosing @code{stage = 3}
+enters at the main loop, so that nothing is changed, and is equivalent
+to performing additional iterations in a previous call.
+@end deftypevar
+
+@deftypevar int mode
+The possible choices are @code{GSL_VEGAS_MODE_IMPORTANCE},
+@code{GSL_VEGAS_MODE_STRATIFIED}, @code{GSL_VEGAS_MODE_IMPORTANCE_ONLY}.
+This determines whether @sc{vegas} will use importance sampling or
+stratified sampling, or whether it can pick on its own.  In low
+dimensions @sc{vegas} uses strict stratified sampling (more precisely,
+stratified sampling is chosen if there are fewer than 2 bins per box).
+@end deftypevar
+
+@deftypevar int verbose
+@deftypevarx {FILE *} ostream
+These parameters set the level of information printed by @sc{vegas}. All
+information is written to the stream @var{ostream}.  The default setting
+of @var{verbose} is @code{-1}, which turns off all output.  A
+@var{verbose} value of @code{0} prints summary information about the
+weighted average and final result, while a value of @code{1} also
+displays the grid coordinates.  A value of @code{2} prints information
+from the rebinning procedure for each iteration.
+@end deftypevar
+
+@node Monte Carlo Examples
+@section Examples
+
+The example program below uses the Monte Carlo routines to estimate the
+value of the following 3-dimensional integral from the theory of random
+walks,
+@tex
+\beforedisplay
+$$
+I = \int_{-\pi}^{+\pi} {dk_x \over 2\pi} 
+    \int_{-\pi}^{+\pi} {dk_y \over 2\pi} 
+    \int_{-\pi}^{+\pi} {dk_z \over 2\pi} 
+     { 1 \over (1 - \cos(k_x)\cos(k_y)\cos(k_z))}.
+$$
+\afterdisplay
+@end tex
+@ifinfo
+
+@example
+I = \int_@{-pi@}^@{+pi@} @{dk_x/(2 pi)@} 
+    \int_@{-pi@}^@{+pi@} @{dk_y/(2 pi)@} 
+    \int_@{-pi@}^@{+pi@} @{dk_z/(2 pi)@} 
+     1 / (1 - cos(k_x)cos(k_y)cos(k_z)).
+@end example
+
+@end ifinfo
+@noindent
+The analytic value of this integral can be shown to be @math{I =
+\Gamma(1/4)^4/(4 \pi^3) = 1.393203929685676859...}.  The integral gives
+the mean time spent at the origin by a random walk on a body-centered
+cubic lattice in three dimensions.
+
+For simplicity we will compute the integral over the region
+@math{(0,0,0)} to @math{(\pi,\pi,\pi)} and multiply by 8 to obtain the
+full result.  The integral is slowly varying in the middle of the region
+but has integrable singularities at the corners @math{(0,0,0)},
+@math{(0,\pi,\pi)}, @math{(\pi,0,\pi)} and @math{(\pi,\pi,0)}.  The
+Monte Carlo routines only select points which are strictly within the
+integration region and so no special measures are needed to avoid these
+singularities.
+
+@smallexample
+@verbatiminclude examples/monte.c
+@end smallexample
+
+@noindent
+With 500,000 function calls the plain Monte Carlo algorithm achieves a
+fractional error of 0.6%.  The estimated error @code{sigma} is
+consistent with the actual error, and the computed result differs from
+the true result by about one standard deviation,
+
+@example
+plain ==================
+result =  1.385867
+sigma  =  0.007938
+exact  =  1.393204
+error  = -0.007337 = 0.9 sigma
+@end example
+
+@noindent
+The @sc{miser} algorithm reduces the error by a factor of two, and also
+correctly estimates the error,
+
+@example
+miser ==================
+result =  1.390656
+sigma  =  0.003743
+exact  =  1.393204
+error  = -0.002548 = 0.7 sigma
+@end example
+
+@noindent
+In the case of the @sc{vegas} algorithm the program uses an initial
+warm-up run of 10,000 function calls to prepare, or ``warm up'', the grid.
+This is followed by a main run with five iterations of 100,000 function
+calls. The chi-squared per degree of freedom for the five iterations are
+checked for consistency with 1, and the run is repeated if the results
+have not converged. In this case the estimates are consistent on the
+first pass.
+
+@example
+vegas warm-up ==================
+result =  1.386925
+sigma  =  0.002651
+exact  =  1.393204
+error  = -0.006278 = 2 sigma
+converging...
+result =  1.392957 sigma =  0.000452 chisq/dof = 1.1
+vegas final ==================
+result =  1.392957
+sigma  =  0.000452
+exact  =  1.393204
+error  = -0.000247 = 0.5 sigma
+@end example
+
+@noindent
+If the value of @code{chisq} had differed significantly from 1 it would
+indicate inconsistent results, with a correspondingly underestimated
+error.  The final estimate from @sc{vegas} (using a similar number of
+function calls) is significantly more accurate than the other two
+algorithms.
+
+@node Monte Carlo Integration References and Further Reading
+@section References and Further Reading
+
+The @sc{miser} algorithm is described in the following article by Press
+and Farrar,
+
+@itemize @asis
+@item
+W.H. Press, G.R. Farrar, @cite{Recursive Stratified Sampling for
+Multidimensional Monte Carlo Integration},
+Computers in Physics, v4 (1990), pp190--195.
+@end itemize
+
+@noindent
+The @sc{vegas} algorithm is described in the following papers,
+
+@itemize @asis
+@item
+G.P. Lepage,
+@cite{A New Algorithm for Adaptive Multidimensional Integration},
+Journal of Computational Physics 27, 192--203, (1978)
+
+@item
+G.P. Lepage,
+@cite{VEGAS: An Adaptive Multi-dimensional Integration Program},
+Cornell preprint CLNS 80-447, March 1980
+@end itemize
+