Appendix F. Computational Statistics Toolbox. The Computational Statistics Toolbox can be downloaded from:
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1 Appendix F Computational Statistics Toolbox The Computational Statistics Toolbox can be downloaded from: Please review the readme file for installation instructions and information on any recent changes. TABLE F.1 Chapter 2 Functions: Probability Distributions Beta Binomial Chi-square Exponential Gamma Normal - univariate Normal - multivariate Poisson Continuous Uniform Weibull Distribution PDF (p) / CDF (c) csbetap, csbetac csbinop, csbinoc cschip, cschic csexpop, csexpoc csgammp, csgammc csnormp, csnormc csevalnorm cspoisp, cspoisc csunifp, csunifc csweibp, csweibc
2 558 Computational Statistics Handbook with MATLAB TABLE F.2 Chapter 3 Functions: Statistics These functions are used to obtain parameter estimates for a distribution. These functions return the quantiles. Other descriptive statistics csbinpar csexpar csgampar cspoipar csunipar csbinoq csexpoq csunifq csweibq csnormq csquantiles csmomentc cskewness cskurtosis csmoment csecdf TABLE F.3 Chapter 4 Functions: Random Number Generation Distribution Beta csbetarnd Binomial csbinrnd Chi-square cschirnd Discrete Uniform csdunrnd Exponential csexprnd Gamma csgamrnd Multivariate Normal csmvrnd Poisson cspoirnd Points on a sphere cssphrnd
3 Appendix F: Computational Statistics Toolbox 559 TABLE F.4 Chapter 5 Functions: Exploratory Data Analysis Star Plot Stem-and-leaf Plot Parallel Coordinates Plot Q-Q Plot Poissonness Plot Andrews Curves Exponential Probability Plot Binomial Plot PPEDA csstars csstemleaf csparallel csqqplot cspoissplot csandrews csexpoplot csbinoplot csppeda csppstrtrem csppind TABLE F.5 Chapter 6 Functions: Bootstrap General bootstrap: resampling, estimates of standard error and bias csboot Constructing bootstrap confidence intervals csbootint csbooperint csbootbca TABLE F.6 Chapter 7 Functions: Jackknife Implements the jackknife and returns the jackknife estimate of standard error and bias Implements the jackknife-after-bootstrap and returns the jackknife estimate of the error in the bootstrap csjack csjackboot
4 560 Computational Statistics Handbook with MATLAB TABLE F.7 Chapter 8 Functions: Probability Density Estimation Bivariate histogram cshist2d cshistden Frequency polygon Averaged Shifted Histogram Kernel density estimation Create plots Finite and adaptive mixtures csfreqpoly csash cskernnd cskern2d csdfplot csplotuni csfinmix csadpmix TABL BLE F.8 Chapter 9 Functions: Statistical Pattern Recognition Creating, pruning and displaying classification trees csgrowc csprunec cstreec csplotreec cspicktreec Creating, analyzing and displaying clusters cshmeans cskmeans Statistical pattern recognition using Bayes decision theory csrocgen cskernmd cskern2d
5 Appendix F: Computational Statistics Toolbox 561 TAB ABLE F.9 Chapter 10 Functions: Nonparametric Regression Loess smoothing Local polynomial smoothing Functions for regression trees Nonparametric regression using kernels csloess csloessenv csloessr cslocpoly csgrowr cspruner cstreer csplotreer cspicktreer csloclin TABLE F.10 Chapter 11 Functions: Markov Chain Monte Carlo Gelman-Rubin convergence diagnostic Graphical demonstration of the Metropolis- Hastings sampler csgelrub csmcmcdemo TABLE F.11 Chapter 12 Functions: Spatial Statistics Functions for generating samples from spatial point processes Interactively find a study region Estimate the intensity using the quartic kernel (no edge effects) Estimating second-order effects of a spatial point pattern csbinproc csclustproc csinhibproc cspoissproc csstraussproc csgetregion csintkern csfhat csghat cskhat
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