matlab统计工具箱函数.doc

% Statistics Toolbox

% betafit - Beta parameter estimation.

% binofit - Binomial parameter estimation.

% dfittool - Distribution fitting tool.

% evfit

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Extreme value parameter estimation.

% expfit - Exponential parameter estimation.

% gamfit - Gamma parameter estimation.

% log nfit

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Log no rmal parameter estimati on.

% mle

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Maximum likelihood estimation (MLE).

% mlecov - Asymptotic covarianee matrix of MLE.

% nbinfit - Negative binomial parameter estimation.

% normfit

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Normal parameter estimation.

% poissfit - Poisson parameter estimation.

% raylfit

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Rayleigh parameter estimation.

% unifit

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Uniform parameter estimation.

% wblfit

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Weibull parameter estimation.

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% Probability density functions (pdf).

% beta pdf - Beta density

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% binopdf - Binomial density

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% chi2pdf - Chi square density

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% evpdf

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Extreme value density.

% exppdf - Exponential density

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% fpdf - F density.

% gampdf - Gamma density

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% geopdf - Geometric density

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% hygepdf - Hypergeometric density

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% log npdf - Log no rmal density.

% mvnpdf - Multivariate normal density

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% nbinpdf - Negative binomial density.

% n cf pdf - Non central F den sity

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% nctpdf - Noncentral t density

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% ncx2pdf - Noncentral Chi-square density.

% normpdf - Normal (Gaussian) density.

% pdf - Density function for a specified distribution.

% poisspdf - Poisson density.

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raylpdf ? Rayleigh density.

% tpdf-T density.

% unidpdf - Discrete uniform density.

% unifpdf - Uniform density

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% wblpdf - Weibull density.

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% Cumulative Distribution functions (cdf).

% betacdf - Beta cdf.

% binocdf

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Binomial cdf.

% cdf - Specified cumulative distribution function.

% chi2cdf - Chi square cdf.

% ecdf - Empirical cdf (Kaplan-Meier estimate).

% evcdf - Extreme value cumulative distribution function.

% expcdf - Exponential cdf.

% fcdf

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F cdf.

% gamcdf - Gamma cdf.

% geocdf - Geometric cdf.

% hygecdf - Hypergeometric cdf.

% logncdf - Log no rmal cdf.

% nbincdf

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Negative binomial cdf.

% ncfcdf - Noncentral F cdf.

% nctcdf

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Noncentral t cdf.

% ncx2cdf - Noncentral Chi-square cdf.

% normcdf

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Normal (Gaussian) cdf.

% poisscdf - Poisson cdf.

% raylcdf - Rayleigh cdf.

% tcdf - T cdf.

% unidcdf

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Discrete uniform cdf.

% unifcdf - Uniform cdf.

% wblcdf

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Weibull cdf.

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% Critical Values of Distribution functions.

% betai nv

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Beta in verse cumulative distributio n function.

% bino inv - Binomial in verse cumulative distributio n function.

% chi2i nv - Chi square in verse cumulative distributio n fun ctio n.

% evinv

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Extreme value inverse cumulative distribution function.

% expi nv

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Exp on ential in verse cumulative distribution functi on.

% finv - F in verse cumulative distributi on function.

% garninv

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Gamma inverse cumulative distribution function.

% geoinv - Geometric inverse cumulative distribution function.

% hygeinv - Hypergeometric inverse cumulative distribution function.

% icdf

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Spec Hied inverse cdf.

% logninv - Lognormal in verse cumulative distribution fun ction.

% nbininv - Negative binomial inverse distribution function.

% ncfinv

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Noncen tral F in verse cumulative distributi on function.

% nctinv - Noncen tral t in verse cumulative distributi on fun ctio n.

% ncx2inv

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Noncentral Chi-square inverse distribution function.

% norminv

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Normal (Gaussia n) in verse cumulative distribution fun ction.

% poissi nv - Poiss on in verse cumulative distributio n function.

% rayli nv - Rayleigh in verse cumulative distributi on function.

% tinv- T in verse cumulative distributio n function.

% un idinv - Discrete un iform in verse cumulative distributi on function.

% unifinv - Uniform in verse cumulative distributi on function. % wblinv

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Weibull in verse cumulative distributi on function.

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% Random Number Generators

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% betarnd - Beta random numbers.

% binornd - Binomial random numbers

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% chi2rnd - Chi square random numbers.

% evrnd - Extreme value random numbers

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% exprnd

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Exponential random numbers

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% frnd - F random numbers

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% gamrnd - Gamma random numbers

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% geornd - Geometric random numbers

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% hygernd - Hypergeometric random numbers

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% iwishrnd

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Inverse Wishart random matrix.

% lognr nd - Log no rmal ran dom numbers.

% mvnrnd

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Multivariate normal random numbers

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% mvtrnd - Multivariate t random numbers.

% nbinrnd - Negative binomial random numbers

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% ncfrnd - Noncentral F random numbers

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% nctrnd

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Noncentral t random numbers.

% ncx2rnd

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Noncentral Chi-square random numbers

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% normrnd - Normal (Gaussian) random numbers

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% poissrnd - Poisson random numbers

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% randg

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Gamma random numbers (unit scale).

% random - Random numbers from specified distribution.

% randsample - Random sample from finite population.

% raylrnd

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Rayleigh random numbers

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% trnd - T random numbers

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% unidrnd

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Discrete urdform random numbers.

% urdfrnd - Uniform random numbers

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% wblrnd

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Weibull random numbers.

% wishrnd

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Wishart random matrix

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% Statistics.

% betastat - Beta mean and variance.

% binostat

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Binomial mean and variance

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% chi2stat - Chi square mean and varianee.

% evstat - Extreme value mean and varianee.

% expstat - Exponential mean and varianee.

% fstat - F mean and variance

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% gamstat - Gamma mean and varianee.

% geostat - Geometric mean and varianee.

% hygestat - Hypergeometric mean and variance

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% lognstat

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Lognormal mean and varianee.

% nbinstat

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Negative binomial mean and varianee.

% n cfstat - Non central F mea n and varia nee.

% nctstat - Noncentral t mean and varianee.

% ncx2stat - Noncentral Chi-square mean and varianee.

% no rmstat - Normal (Gaussia n) mea n and varia nee.

% poisstat - Poisson mean and varianee.

% raylstat - Rayleigh mean and varianee.

% tstat - T mean and varianee.

% unidstat

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Discrete uniform mean and variance

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% unifstat - Uniform mean and varianee.

% wblstat

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Weibull mean and variance

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% Likelihood functions.

% beta I ike

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Negative beta log-likelihood

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% evlike - Negative extreme value log- likelihood.

% exp I ike - Negative exp on ential log-likelihood

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% gamlike - Negative gamma log- likelihood.

% log nlike - Negative log normal log-likelihood

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% nbinlike - Negative likelihood for negative binomial distribution.

% normlike

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Negative normal likelihood

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% wbllike - Negative Weibull log-likelihood.

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% Descriptive Statistics.

% bootstrp

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Bootstrap statistics for any function.

% corr

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Lin ear or rank correlati on coefficie nt.

% corrcoef - Lin ear correlati on coefficie nt with con fide nee intervals.

% cov - Covariance.

% crosstab - Cross tabulation.

% geomean

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Geometric mean.

% grpstats - Summary statistics by group.

% harmmean - Harmonic mean.

% iqr

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In terquartile range.

% kurtosis - Kurtosis

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% mad

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Median Absolute Deviation.

% mean - Sample average (in MATLAB toolbox).

% median - 50th percentile of a sample.

% moment

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Moments of a sample.

% nan max - Maximum ignoring NaNs

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% nan mean

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Mea n ign oring NaNs

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% nan media n - Median igno ring NaNs

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% nanmin - Minimum ignoring NaNs.

% nanstd - Standard deviation ignoring NaNs

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% nan sum - Sum ignoring NaNs.

% nanvar - Variance ignoring NaNs.

% pretile - Percentiles.

% quantile

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Quantiles

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% range - Range.

% skewness

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Skewness.

% std - Standard deviation (in MATLAB toolbox).

% tabulate - Frequency table

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% trimmean - Trimmed mean.

% var

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Variance (in MATLAB toolbox).

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% Linear Models.

% addedvarplot - Created added-variable plot for stepwise regression.

% anoval

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One-way analysis of variance

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% anova2

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Two-way analysis of varianee.

% a nova n

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n-way analysis of variance

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% aoctool -1nteractive tool for analysis of covariance.

% dummyvar - Dummy-variable coding.

% friedman

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Friedmarfs test (nonparametric two-way anova).

% glmfit - Generalized linear model fitting.

% glmval

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Evaluate fitted values for generalized linear model.

% kruskalwallis - Kruskal-Wallis test (nonparametric one-way anova).

% leverage - Regression diagnostic

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% Iscov

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Least-squares estimates with known covarianee matrix

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% Isqnonneg - Non

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negative least-squares

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% manoval - One-way multivariate analysis of varianee.

% manovacluster

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Draw clusters of group means for manoval.

% multcompare - Multiple comparisons of means and other estimates

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% polyc onf

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Polyno mial evaluati on and con fide nee interval estimatio n.

% polyfit

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Least-squares polynomial fitting.

% polyval - Predicted values for polynomial functions.

% rcoplot - Residuals case order plot.

% regress

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Multivariate linear regression.

% regstats - Regression diag no sties.

% ridge - Ridge regression.

% robustfit

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Robust regression model fitting.

% rstool - Multidimensional response surface visualization (RSIVI).

% stepwise - Interactive tool for stepwise regression.

% stepwisefit - Non-interactive stepwise regression.

% x2fx - Factor settings matrix (x) to design matrix (fx).

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% Nonlinear Models

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% nlinfit - Nonlinear least-squares data fitting.

% nlin tool

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Interactive graphical tool for prediction in non linear models.

% n Ipredci - Con fide nee intervals for predictio n.