progs.htm

这是数学计算上常用的计算方法

 (<a href="examples/xzroots.cpp">example</a>)<li>[9.5]
<a href="recipes/zrhqr.cpp"><b>zrhqr</b></a> roots of a polynomial by eigenvalue methods
 (<a href="examples/xzrhqr.cpp">example</a>)<li>[9.5]
<a href="recipes/qroot.cpp"><b>qroot</b></a> complex or double root of a polynomial, Bairstow
 (<a href="examples/xqroot.cpp">example</a>)<li>[9.6]
<a href="recipes/mnewt.cpp"><b>mnewt</b></a> Newton's method for systems of equations
 (<a href="examples/xmnewt.cpp">example</a>)<li>[9.7]
<a href="recipes/lnsrch.cpp"><b>lnsrch</b></a> search along a line, used by newt
<li>[9.7]
<a href="recipes/newt.cpp"><b>newt</b></a> globally convergent multi-dimensional Newton's method
 (<a href="examples/xnewt.cpp">example</a>)<li>[9.7]
<a href="recipes/fdjac.cpp"><b>fdjac</b></a> finite-difference Jacobian, used by newt
<li>[9.7]
<a href="recipes/fmin.cpp"><b>fmin</b></a> norm of a vector function, used by newt
<li>[9.7]
<a href="recipes/broydn.cpp"><b>broydn</b></a> secant method for systems of equations
 (<a href="examples/xbroydn.cpp">example</a>)</menu>
<h3><a name="C10"></A><A HREF="toc.htm#C10">Chapter
10</a></h3>
<menu>
<li>[10.1]
<a href="recipes/mnbrak.cpp"><b>mnbrak</b></a> bracket the minimum of a function
 (<a href="examples/xmnbrak.cpp">example</a>)<li>[10.1]
<a href="recipes/golden.cpp"><b>golden</b></a> find minimum of a function by golden section search
 (<a href="examples/xgolden.cpp">example</a>)<li>[10.2]
<a href="recipes/brent.cpp"><b>brent</b></a> find minimum of a function by Brent's method
 (<a href="examples/xbrent.cpp">example</a>)<li>[10.3]
<a href="recipes/dbrent.cpp"><b>dbrent</b></a> find minimum of a function using derivative information
 (<a href="examples/xdbrent.cpp">example</a>)<li>[10.4]
<a href="recipes/amoeba.cpp"><b>amoeba</b></a> minimize in N-dimensions by downhill simplex method
 (<a href="examples/xamoeba.cpp">example</a>)<li>[10.4]
<a href="recipes/amotry.cpp"><b>amotry</b></a> evaluate a trial point, used by amoeba
<li>[10.5]
<a href="recipes/powell.cpp"><b>powell</b></a> minimize in N-dimensions by  Powell's method
 (<a href="examples/xpowell.cpp">example</a>)<li>[10.5]
<a href="recipes/linmin.cpp"><b>linmin</b></a> minimum of a function along a ray in N-dimensions
 (<a href="examples/xlinmin.cpp">example</a>)<li>[10.5]
<a href="recipes/f1dim.cpp"><b>f1dim</b></a> function used by LINMIN
 (<a href="examples/xf1dim.cpp">example</a>)<li>[10.6]
<a href="recipes/frprmn.cpp"><b>frprmn</b></a> minimize in N-dimensions by conjugate gradient
 (<a href="examples/xfrprmn.cpp">example</a>)<li>[10.6]
<a href="recipes/df1dim.cpp"><b>df1dim</b></a> alternative function used by LINMIN
 (<a href="examples/xdf1dim.cpp">example</a>)<li>[10.7]
<a href="recipes/dfpmin.cpp"><b>dfpmin</b></a> minimize in N-dimensions by variable metric method
 (<a href="examples/xdfpmin.cpp">example</a>)<li>[10.8]
<a href="recipes/simplx.cpp"><b>simplx</b></a> linear programming maximization of a linear function
 (<a href="examples/xsimplx.cpp">example</a>)<li>[10.8]
<a href="recipes/simp1.cpp"><b>simp1</b></a> linear programming, used by SIMPLX
<li>[10.8]
<a href="recipes/simp2.cpp"><b>simp2</b></a> linear programming, used by SIMPLX
<li>[10.8]
<a href="recipes/simp3.cpp"><b>simp3</b></a> linear programming, used by SIMPLX
<li>[10.9]
<a href="recipes/anneal.cpp"><b>anneal</b></a> traveling salesman problem by simulated annealing
 (<a href="examples/xanneal.cpp">example</a>)<li>[10.9]
<a href="recipes/revcst.cpp"><b>revcst</b></a> cost of a reversal, used by anneal
<li>[10.9]
<a href="recipes/reverse.cpp"><b>reverse</b></a> do a reversal, used by anneal
<li>[10.9]
<a href="recipes/trncst.cpp"><b>trncst</b></a> cost of a transposition, used by anneal
<li>[10.9]
<a href="recipes/trnspt.cpp"><b>trnspt</b></a> do a transposition, used by anneal
<li>[10.9]
<a href="recipes/metrop.cpp"><b>metrop</b></a> Metropolis algorithm, used by anneal
<li>[10.9]
<a href="recipes/amebsa.cpp"><b>amebsa</b></a> simulated annealing in continuous spaces
 (<a href="examples/xamebsa.cpp">example</a>)<li>[10.9]
<a href="recipes/amotsa.cpp"><b>amotsa</b></a> evaluate a trial point, used by amebsa
</menu>
<h3><a name="C11"></A><A HREF="toc.htm#C11">Chapter
11</a></h3>
<menu>
<li>[11.1]
<a href="recipes/jacobi.cpp"><b>jacobi</b></a> eigenvalues and eigenvectors of a symmetric matrix
 (<a href="examples/xjacobi.cpp">example</a>)<li>[11.1]
<a href="recipes/eigsrt.cpp"><b>eigsrt</b></a> eigenvectors, sorts into order by eigenvalue
 (<a href="examples/xeigsrt.cpp">example</a>)<li>[11.2]
<a href="recipes/tred2.cpp"><b>tred2</b></a> Householder reduction of a real, symmetric matrix
 (<a href="examples/xtred2.cpp">example</a>)<li>[11.3]
<a href="recipes/tqli.cpp"><b>tqli</b></a> eigensolution of a symmetric tridiagonal matrix
 (<a href="examples/xtqli.cpp">example</a>)<li>[11.5]
<a href="recipes/balanc.cpp"><b>balanc</b></a> balance a nonsymmetric matrix
 (<a href="examples/xbalanc.cpp">example</a>)<li>[11.5]
<a href="recipes/elmhes.cpp"><b>elmhes</b></a> reduce a general matrix to Hessenberg form
 (<a href="examples/xelmhes.cpp">example</a>)<li>[11.6]
<a href="recipes/hqr.cpp"><b>hqr</b></a> eigenvalues of a Hessenberg matrix
 (<a href="examples/xhqr.cpp">example</a>)</menu>
<h3><a name="C12"></A><A HREF="toc.htm#C12">Chapter
12</a></h3>
<menu>
<li>[12.2]
<a href="recipes/four1.cpp"><b>four1</b></a> fast Fourier transform (FFT) in one dimension
 (<a href="examples/xfour1.cpp">example</a>)<li>[12.3]
<a href="recipes/twofft.cpp"><b>twofft</b></a> fast Fourier transform of two real functions
 (<a href="examples/xtwofft.cpp">example</a>)<li>[12.3]
<a href="recipes/realft.cpp"><b>realft</b></a> fast Fourier transform of a single real function
 (<a href="examples/xrealft.cpp">example</a>)<li>[12.3]
<a href="recipes/sinft.cpp"><b>sinft</b></a> fast sine transform
 (<a href="examples/xsinft.cpp">example</a>)<li>[12.3]
<a href="recipes/cosft1.cpp"><b>cosft1</b></a> fast cosine transform with endpoints
 (<a href="examples/xcosft1.cpp">example</a>)<li>[12.3]
<a href="recipes/cosft2.cpp"><b>cosft2</b></a> ``staggered'' fast cosine transform
 (<a href="examples/xcosft2.cpp">example</a>)<li>[12.4]
<a href="recipes/fourn.cpp"><b>fourn</b></a> fast Fourier transform in multidimensions
 (<a href="examples/xfourn.cpp">example</a>)<li>[12.5]
<a href="recipes/rlft3.cpp"><b>rlft3</b></a> FFT of real data in two or three dimensions
 (<a href="examples/xrlft3.cpp">example</a>)<li>[12.6]
<a href="recipes/fourfs.cpp"><b>fourfs</b></a> FFT for huge data sets on external media
 (<a href="examples/xfourfs.cpp">example</a>)<li>[12.6]
<a href="recipes/fourew.cpp"><b>fourew</b></a> rewind and permute files, used by fourfs
</menu>
<h3><a name="C13"></A><A HREF="toc.htm#C13">Chapter
13</a></h3>
<menu>
<li>[13.1]
<a href="recipes/convlv.cpp"><b>convlv</b></a> convolution or deconvolution of data using FFT
 (<a href="examples/xconvlv.cpp">example</a>)<li>[13.2]
<a href="recipes/correl.cpp"><b>correl</b></a> correlation or autocorrelation of data using FFT
 (<a href="examples/xcorrel.cpp">example</a>)<li>[13.4]
<a href="recipes/spctrm.cpp"><b>spctrm</b></a> power spectrum estimation using FFT
 (<a href="examples/xspctrm.cpp">example</a>)<li>[13.6]
<a href="recipes/memcof.cpp"><b>memcof</b></a> evaluate maximum entropy (MEM) coefficients
 (<a href="examples/xmemcof.cpp">example</a>)<li>[13.6]
<a href="recipes/fixrts.cpp"><b>fixrts</b></a> reflect roots of a polynomial into unit circle
 (<a href="examples/xfixrts.cpp">example</a>)<li>[13.6]
<a href="recipes/predic.cpp"><b>predic</b></a> linear prediction using MEM coefficients
 (<a href="examples/xpredic.cpp">example</a>)<li>[13.7]
<a href="recipes/evlmem.cpp"><b>evlmem</b></a> power spectral estimation from MEM coefficients
 (<a href="examples/xevlmem.cpp">example</a>)<li>[13.8]
<a href="recipes/period.cpp"><b>period</b></a> power spectrum of unevenly sampled data
 (<a href="examples/xperiod.cpp">example</a>)<li>[13.8]
<a href="recipes/fasper.cpp"><b>fasper</b></a> power spectrum of unevenly sampled larger data sets
 (<a href="examples/xfasper.cpp">example</a>)<li>[13.8]
<a href="recipes/spread.cpp"><b>spread</b></a> extirpolate value into array, used by fasper
<li>[13.9]
<a href="recipes/dftcor.cpp"><b>dftcor</b></a> compute endpoint corrections for Fourier integrals
<li>[13.9]
<a href="recipes/dftint.cpp"><b>dftint</b></a> high-accuracy Fourier integrals
 (<a href="examples/xdftint.cpp">example</a>)<li>[13.10]
<a href="recipes/wt1.cpp"><b>wt1  </b></a> one-dimensional discrete wavelet transform
<li>[13.10]
<a href="recipes/daub4.cpp"><b>daub4</b></a> Daubechies 4-coefficient wavelet filter
<li>[13.10]
<a href="recipes/pwtset.cpp"><b>pwtset</b></a> initialize coefficients for pwt
<li>[13.10]
<a href="recipes/pwt.cpp"><b>pwt  </b></a> partial wavelet transform
<li>[13.10]
<a href="recipes/wtn.cpp"><b>wtn  </b></a> multidimensional discrete wavelet transform
</menu>
<h3><a name="C14"></A><A HREF="toc.htm#C14">Chapter
14</a></h3>
<menu>
<li>[14.1]
<a href="recipes/moment.cpp"><b>moment</b></a> calculate moments of a data set
 (<a href="examples/xmoment.cpp">example</a>)<li>[14.2]
<a href="recipes/ttest.cpp"><b>ttest</b></a> Student's t-test for difference of means
 (<a href="examples/xttest.cpp">example</a>)<li>[14.2]
<a href="recipes/avevar.cpp"><b>avevar</b></a> calculate mean and variance of a data set
 (<a href="examples/xavevar.cpp">example</a>)<li>[14.2]
<a href="recipes/tutest.cpp"><b>tutest</b></a> Student's t-test for means, case of unequal variances
 (<a href="examples/xtutest.cpp">example</a>)<li>[14.2]
<a href="recipes/tptest.cpp"><b>tptest</b></a> Student's t-test for means, case of paired data
 (<a href="examples/xtptest.cpp">example</a>)<li>[14.2]
<a href="recipes/ftest.cpp"><b>ftest</b></a> F-test for difference of variances
 (<a href="examples/xftest.cpp">example</a>)<li>[14.3]
<a href="recipes/chsone.cpp"><b>chsone</b></a> chi-square test for difference between data and model
 (<a href="examples/xchsone.cpp">example</a>)<li>[14.3]
<a href="recipes/chstwo.cpp"><b>chstwo</b></a> chi-square test for difference between two data sets
 (<a href="examples/xchstwo.cpp">example</a>)<li>[14.3]
<a href="recipes/ksone.cpp"><b>ksone</b></a> Kolmogorov-Smirnov test of data against model
 (<a href="examples/xksone.cpp">example</a>)<li>[14.3]
<a href="recipes/kstwo.cpp"><b>kstwo</b></a> Kolmogorov-Smirnov test between two data sets
 (<a href="examples/xkstwo.cpp">example</a>)<li>[14.3]
<a href="recipes/probks.cpp"><b>probks</b></a> Kolmogorov-Smirnov probability function
 (<a href="examples/xprobks.cpp">example</a>)<li>[14.4]
<a href="recipes/cntab1.cpp"><b>cntab1</b></a> contingency table analysis using chi-square
 (<a href="examples/xcntab1.cpp">example</a>)<li>[14.4]
<a href="recipes/cntab2.cpp"><b>cntab2</b></a> contingency table analysis using entropy measure
 (<a href="examples/xcntab2.cpp">example</a>)<li>[14.5]
<a href="recipes/pearsn.cpp"><b>pearsn</b></a> Pearson's correlation between two data sets
 (<a href="examples/xpearsn.cpp">example</a>)<li>[14.6]
<a href="recipes/spear.cpp"><b>spear</b></a> Spearman's rank correlation between two data sets
 (<a href="examples/xspear.cpp">example</a>)<li>[14.6]
<a href="recipes/crank.cpp"><b>crank</b></a> replaces array elements by their rank
 (<a href="examples/xcrank.cpp">example</a>)<li>[14.6]
<a href="recipes/kendl1.cpp"><b>kendl1</b></a> correlation between two data sets, Kendall's tau
 (<a href="examples/xkendl1.cpp">example</a>)<li>[14.6]
<a href="recipes/kendl2.cpp"><b>kendl2</b></a> contingency table analysis using Kendall's tau
 (<a href="examples/xkendl2.cpp">example</a>)<li>[14.7]
<a href="recipes/ks2d1s.cpp"><b>ks2d1s</b></a> K--S test in two dimensions, data vs. model
 (<a href="examples/xks2d1s.cpp">example</a>)<li>[14.7]
<a href="recipes/quadct.cpp"><b>quadct</b></a> count points by quadrants, used by ks2d1s
<li>[14.7]
<a href="recipes/quadvl.cpp"><b>quadvl</b></a> quadrant probabilities, used by ks2d1s