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| [https://gnu-octave.github.io/statistics/confusionmat.html confusionmat]
| [https://gnu-octave.github.io/statistics/confusionmat.html confusionmat]
| Compute a confusion matrix for classification problems.
| Compute a confusion matrix for classification problems.
|-
| [https://gnu-octave.github.io/statistics/ConfusionMatrixChart.html ConfusionMatrixChart]
| Compute a ConfusionMatrixChart class object.
|-
|-
| [https://gnu-octave.github.io/statistics/cophenet.html cophenet]
| [https://gnu-octave.github.io/statistics/cophenet.html cophenet]
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| [https://gnu-octave.github.io/statistics/pdist2.html pdist2]
| [https://gnu-octave.github.io/statistics/pdist2.html pdist2]
| Compute pairwise distance between two sets of vectors.
| Compute pairwise distance between two sets of vectors.
|-
| [https://gnu-octave.github.io/statistics/procrustes.html procrustes]
| Procrustes Analysis.
|-
|-
| [https://gnu-octave.github.io/statistics/slicesample.html slicesample]
| [https://gnu-octave.github.io/statistics/slicesample.html slicesample]
Line 97: Line 91:
| Randomly sample data.
| Randomly sample data.
|-
|-
| [https://gnu-octave.github.io/statistics/fillmissing.html fillmissing]
| https://gnu-octave.github.io/statistics/grp2idx.html grp2idx]
| Replace missing entries of array A either with values in v or as determined by other specified methods.
|-
| [https://gnu-octave.github.io/statistics/grp2idx.html grp2idx]
| Get index for group variables.
| Get index for group variables.
|-
| [https://gnu-octave.github.io/statistics/ismissing.html ismissing]
| Find missing data in a numeric or string array.
|-
| [https://gnu-octave.github.io/statistics/normalise_distribution.html normalise_distribution]
|  Transform a set of data so as to be N(0,1) distributed according to an idea by van Albada and Robinson.
|-
| [https://gnu-octave.github.io/statistics/rmmissing.html rmmissing]
| Remove missing or incomplete data from an array.
|-
| [https://gnu-octave.github.io/statistics/standardizeMissing.html standardizeMissing]
| Replace data values specified by indicator in A by the standard ’missing’ data value for that data type.
|-
|-
| [https://gnu-octave.github.io/statistics/tabulate.html tabulate]
| [https://gnu-octave.github.io/statistics/tabulate.html tabulate]
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! Description
! Description
|-
|-
| [https://gnu-octave.github.io/statistics/cl_multinom.html cl_multinom]
| geomean
| Confidence level of multinomial portions.
|-
| [https://gnu-octave.github.io/statistics/geomean.html geomean]
| Compute the geometric mean.
| Compute the geometric mean.
|-
|-
| [https://gnu-octave.github.io/statistics/grpstats.html grpstats]
| grpstats
| Compute summary statistics by group. Fully MATLAB compatible.
| Compute summary statistics by group. Fully MATLAB compatible.
|-
|-
| [https://gnu-octave.github.io/statistics/harmmean.html harmmean]
| harmmean
| Compute the harmonic mean.
| Compute the harmonic mean.
|-
|-
| [https://gnu-octave.github.io/statistics/jackknife.html jackknife]
| jackknife
| Compute jackknife estimates of a parameter taking one or more given samples as parameters.
| Compute jackknife estimates of a parameter taking one or more given samples as parameters.
|-
|-
| [https://gnu-octave.github.io/statistics/mean.html mean]
| mean
| Compute the mean. Fully MATLAB compatible.
| Compute the mean. Fully MATLAB compatible.
|-
|-
| [https://gnu-octave.github.io/statistics/median.html median]
| median
| Compute the median. Fully MATLAB compatible.
| Compute the median. Fully MATLAB compatible.
|-
|-
| [https://gnu-octave.github.io/statistics/nanmax.html nanmax]
| nanmax
| Find the maximal element while ignoring NaN values.
| Find the maximal element while ignoring NaN values.
|-
|-
| [https://gnu-octave.github.io/statistics/nanmin.html nanmin]
| nanmin
| Find the minimal element while ignoring NaN values.
| Find the minimal element while ignoring NaN values.
|-
|-
| [https://gnu-octave.github.io/statistics/nansum.html nansum]
| nansum
| Compute the sum while ignoring NaN values.
| Compute the sum while ignoring NaN values.
|-
|-
| [https://gnu-octave.github.io/statistics/std.html std]
| std
| Compute the standard deviation. Fully MATLAB compatible.
| Compute the standard deviation. Fully MATLAB compatible.
|-
|-
| [https://gnu-octave.github.io/statistics/trimmean.html trimmean]
| trimmean
| Compute the trimmed mean.
| Compute the trimmed mean.
|-
|-
| [https://gnu-octave.github.io/statistics/var.html std]
| std
| Compute the variance. Fully MATLAB compatible.
| Compute the variance. Fully MATLAB compatible.
|}
|}
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=== In external packages ===
=== In external packages ===


<code>bootci</code>, <code>bootstrp</code> are implemented in the [https://gnu-octave.github.io/packages/statistics-resampling statistics-resampling] package.
<code>bootci</code>, <code>bootstrp</code> are implemented in the [https://gnu-octave.github.io/packages/statistics-bootstrap statistics-bootstrap] package.


=== Shadowing Octave core functions ===
=== Shadowing Octave core functions ===
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| binornd  
| binornd  
|-
|-
| [https://en.wikipedia.org/wiki/Joint_probability_distribution Bivariate Normal]
| [https://en.wikipedia.org/wiki/Joint_probability_distribution Bivariate]
| bvncdf
| bvncdf
|
|
|
|-
| [https://en.wikipedia.org/wiki/Joint_probability_distribution Bivariate Student's <i>t</i>]
| bvtcdf
|
|
|
|
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| mvnrnd
| mvnrnd
|-
|-
| [https://en.wikipedia.org/wiki/Multivariate_t-distribution Multivariate Student's <i>t</i>]
| [https://en.wikipedia.org/wiki/Multivariate_t-distribution Multivariate Student's T]
| mvtcdf mvtcdfqmc
| mvtcdf mvtcdfqmc
| mvtinv
| mvtinv
Line 383: Line 353:
| ncfrnd
| ncfrnd
|-
|-
| [https://en.wikipedia.org/wiki/Noncentral_t-distribution Noncentral Student's <i>t</i>]
| [https://en.wikipedia.org/wiki/Noncentral_t-distribution Noncentral Student's T]
| nctcdf
| nctcdf
| nctinv
| nctinv
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| stdnormal_rnd
| stdnormal_rnd
|-
|-
| [https://en.wikipedia.org/wiki/Student%27s_t-distribution Student's <i>t</i>]
| [https://en.wikipedia.org/wiki/Student%27s_t-distribution Student's T]
| tcdf
| tcdf
| tinv
| tinv
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== Experimental Design ==
== Experimental Design ==
=== Available functions ===


Functions available for computing design matrices.
Functions available for computing design matrices.
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! Description
! Description
|-
|-
| [https://gnu-octave.github.io/statistics/fullfact.html fullfact]
| fullfact
| Full factorial design.
| Full factorial design.
|-
|-
| [https://gnu-octave.github.io/statistics/ff2n.html ff2n]
| ff2n
| Two-level full factorial design.
| Two-level full factorial design.
|-
|-
| [https://gnu-octave.github.io/statistics/sigma_pts.html sigma_pts]
| sigma_pts
| Calculates 2*N+1 sigma points in N dimensions.
| Calculates 2*N+1 sigma points in N dimensions.
|-
|-
| [https://gnu-octave.github.io/statistics/x2fx.html x2fx]
| x2fx
| Convert predictors to design matrix.
| Convert predictors to design matrix.
|}
|}
== Machine Learning ==
=== Available functions ===
The following table lists the available functions.
{| class="wikitable"
! Function
! Description
|-
| [https://gnu-octave.github.io/statistics/hmmestimate.html hmmestimate]
| Estimation of a hidden Markov model for a given sequence.
|-
| [https://gnu-octave.github.io/statistics/hmmgenerate.html hmmgenerate]
| Output sequence and hidden states of a hidden Markov model.
|-
| [https://gnu-octave.github.io/statistics/hmmviterbi.html hmmviterbi]
| Viterbi path of a hidden Markov model.
|-
| [https://gnu-octave.github.io/statistics/svmpredict.html svmpredict]
| Perform a K-means clustering of an NxD matrix.
|-
| [https://gnu-octave.github.io/statistics/svmtrain.html svmtrain]
| Produce a hierarchical clustering dendrogram.
|}
=== TODO list ===
Update <code>svmpredict</code> and <code>svmtrain</code> to libsvm 3.0.
Missing functions:
<div style="column-count:1;-moz-column-count:1;-webkit-column-count:1">
* <code>hmmdecode</code>
* <code>hmmtrain</code>
</div>


== Model Fitting ==
== Model Fitting ==
=== Available functions ===


Functions available for fitting or evaluating statistical models.  
Functions available for fitting or evaluating statistical models.  
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! Description
! Description
|-
|-
| [https://gnu-octave.github.io/statistics/crossval.html crossval]
| crossval
| Perform cross validation on given data.
| Perform cross validation on given data.
|-
|-
| [https://gnu-octave.github.io/statistics/fitgmdist.html fitgmdist]
| fitgmdist
| Fit a Gaussian mixture model with K components to DATA.
| Fit a Gaussian mixture model with K components to DATA.
|-
|-
| [https://gnu-octave.github.io/statistics/fitlm.html fitlm]
| fitlm
| Regress the continuous outcome (i.e.  dependent variable) Y on continuous or categorical predictors (i.e.  independent variables) X by minimizing the sum-of-squared residuals.
| Regress the continuous outcome (i.e.  dependent variable) Y on continuous or categorical predictors (i.e.  independent variables) X by minimizing the sum-of-squared residuals.
|}
|}
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== Hypothesis Testing ==
== Hypothesis Testing ==
=== Available functions ===


Functions available for hypothesis testing
Functions available for hypothesis testing
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! Description
! Description
|-
|-
| [https://gnu-octave.github.io/statistics/adtest.html adtest]
| adtest
| Anderson-Darling goodness-of-fit hypothesis test.
| Anderson-Darling goodness-of-fit hypothesis test.
|-
|-
| [https://gnu-octave.github.io/statistics/anova1.html anova1]
| anova1
| Perform a one-way analysis of variance (ANOVA)
| Perform a one-way analysis of variance (ANOVA)
|-
|-
| [https://gnu-octave.github.io/statistics/anova2.html anova2]
| anova2
| Performs two-way factorial (crossed) or a nested analysis of variance (ANOVA) for balanced designs.
| Performs two-way factorial (crossed) or a nested analysis of variance (ANOVA) for balanced designs.
|-
|-
| [https://gnu-octave.github.io/statistics/anovan.html anovan]
| anovan
| Perform a multi (N)-way analysis of (co)variance (ANOVA or ANCOVA) to evaluate the effect of one or more categorical or continuous predictors (i.e.  independent variables) on a continuous outcome (i.e.  dependent variable).
| Perform a multi (N)-way analysis of (co)variance (ANOVA or ANCOVA) to evaluate the effect of one or more categorical or continuous predictors (i.e.  independent variables) on a continuous outcome (i.e.  dependent variable).
|-
|-
| [https://gnu-octave.github.io/statistics/bartlett_test.html bartlett_test]
| bartlett_test
| Perform a Bartlett test for the homogeneity of variances.
| Perform a Bartlett test for the homogeneity of variances.
|-
|-
| [https://gnu-octave.github.io/statistics/barttest.html barttest]
| barttest
| Bartlett's test of sphericity for correlation.
| Bartlett's test of sphericity for correlation.
|-
|-
| [https://gnu-octave.github.io/statistics/binotest.html binotest]
| binotest
| Test for probability P of a binomial sample
| Test for probability P of a binomial sample
|-
|-
| [https://gnu-octave.github.io/statistics/chi2gof.html chi2gof]
| chi2gof
| Chi-square goodness-of-fit test.
| Chi-square goodness-of-fit test.
|-
|-
| [https://gnu-octave.github.io/statistics/chi2test.html chi2test]
| chi2test
| Perform a chi-squared test (for independence or homogeneity).
| Perform a chi-squared test (for independence or homogeneity).
|-
|-
| [https://gnu-octave.github.io/statistics/correlation_test.html correlation_test]
| friedman
| Perform a correlation coefficient test whether two samples x and y come from uncorrelated populations.
|-
| [https://gnu-octave.github.io/statistics/fishertest.html fishertest]
| Fisher’s exact test.
|-
| [https://gnu-octave.github.io/statistics/friedman.html friedman]
| Performs the nonparametric Friedman's test to compare column effects in a two-way layout.
| Performs the nonparametric Friedman's test to compare column effects in a two-way layout.
|-
|-
| [https://gnu-octave.github.io/statistics/hotelling_t2test.html hotelling_t2test]
| hotelling_t2test
| Compute Hotelling's T^2 ("T-squared") test for a single sample or two dependent samples (paired-samples).
| Compute Hotelling's T^2 ("T-squared") test for a single sample or two dependent samples (paired-samples).
|-
|-
| [https://gnu-octave.github.io/statistics/hotelling_t2test2.html hotelling_t2test2]
| hotelling_t2test2
| Compute Hotelling's T^2 ("T-squared") test for two independent samples.
| Compute Hotelling's T^2 ("T-squared") test for two independent samples.
|-
|-
| [https://gnu-octave.github.io/statistics/kruskalwallis.html kruskalwallis]
| kruskalwallis
| Perform a Kruskal-Wallis test, the non-parametric alternative of a one-way analysis of variance (ANOVA).
| Perform a Kruskal-Wallis test, the non-parametric alternative of a one-way analysis of variance (ANOVA).
|-
|-
| [https://gnu-octave.github.io/statistics/kstest.html kstest]
| kstest
| Single sample Kolmogorov-Smirnov (K-S) goodness-of-fit hypothesis test.
| Single sample Kolmogorov-Smirnov (K-S) goodness-of-fit hypothesis test.
|-
|-
| [https://gnu-octave.github.io/statistics/kstest2.html kstest2]
| kstest2
| Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test.
| Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test.
|-
|-
| [https://gnu-octave.github.io/statistics/levene_test.html levene_test]
| levene_test
| Perform a Levene's test for the homogeneity of variances.
| Perform a Levene's test for the homogeneity of variances.
|-
|-
| [https://gnu-octave.github.io/statistics/manova1.html manova1]
| manova1
| One-way multivariate analysis of variance (MANOVA).
| One-way multivariate analysis of variance (MANOVA).
|-
|-
| [https://gnu-octave.github.io/statistics/multcompare.html multcompare]
| multcompare
| Perform posthoc multiple comparison tests or p-value adjustments to control the family-wise error rate (FWER) or false discovery rate (FDR).
| Perform posthoc multiple comparison tests or p-value adjustments to control the family-wise error rate (FWER) or false discovery rate (FDR).
|-
|-
| [https://gnu-octave.github.io/statistics/ranksum.html ranksum]
| ranksum
| Wilcoxon rank sum test for equal medians.  This test is equivalent to a Mann-Whitney U-test.
| Wilcoxon rank sum test for equal medians.  This test is equivalent to a Mann-Whitney U-test.
|-
|-
| [https://gnu-octave.github.io/statistics/regression_ftest.html regression_ftest]
| regression_ftest
| F-test for General Linear Regression Analysis
| F-test for General Linear Regression Analysis
|-
|-
| [https://gnu-octave.github.io/statistics/regression_ttest.html regression_ttest]
| regression_ttest
| Perform a linear regression t-test.
| Perform a linear regression t-test for the null hypothesis ''RR * B = R'' in a classical normal regression model ''Y = X * B + E''.
|-
|-
| [https://gnu-octave.github.io/statistics/runstest.html runstest]
| runstest
| Runs test for detecting serial correlation in the vector X.
| Runs test for detecting serial correlation in the vector X.
|-
|-
| [https://gnu-octave.github.io/statistics/sampsizepwr.html sampsizepwr]
| sampsizepwr
| Sample size and power calculation for hypothesis test.
| Sample size and power calculation for hypothesis test.
|-
|-
| [https://gnu-octave.github.io/statistics/signtest.html signtest]
| signtest
| Test for median.
| Test for median.
|-
|-
| [https://gnu-octave.github.io/statistics/ttest.html ttest]
| ttest
| Test for mean of a normal sample with unknown variance or a paired-sample t-test.
| Test for mean of a normal sample with unknown variance or a paired-sample t-test.
|-
|-
| [https://gnu-octave.github.io/statistics/ttest2.html ttest2]
| ttest2
| Perform a two independent samples t-test.
| Perform a two independent samples t-test.
|-
|-
| [https://gnu-octave.github.io/statistics/vartest.html vartest]
| vartest
| One-sample test of variance.
| One-sample test of variance.
|-
|-
| [https://gnu-octave.github.io/statistics/vartest2.html vartest2]
| vartest2
| Two-sample F test for equal variances.
| Two-sample F test for equal variances.
|-
|-
| [https://gnu-octave.github.io/statistics/vartestn.html vartestn]
| vartestn
| Test for equal variances across multiple groups.
| Test for equal variances across multiple groups.
|-
|-
| [https://gnu-octave.github.io/statistics/ztest.html ztest]
| ztest
| One-sample Z-test.
| One-sample Z-test.
|-
| [https://gnu-octave.github.io/statistics/ztest2.html ztest2]
| Two proportions Z-test.
|}
|}


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* <code>fishertest</code>
* <code>fishertest</code>
* <code>meanEffectSize</code>
* <code>meanEffectSize</code>
</div>
== Machine Learning ==
=== Available functions ===
The following table lists the available functions.
{| class="wikitable"
! Function
! Description
|-
| hmmestimate
| Estimation of a hidden Markov model for a given sequence.
|-
| hmmgenerate
| Output sequence and hidden states of a hidden Markov model.
|-
| hmmviterbi
| Viterbi path of a hidden Markov model.
|-
| svmpredict
| Perform a K-means clustering of an NxD matrix.
|-
| svmtrain
| Produce a hierarchical clustering dendrogram.
|}
=== TODO list ===
Update <code>svmpredict</code> and <code>svmtrain</code> to libsvm 3.0.
Missing functions:
<div style="column-count:1;-moz-column-count:1;-webkit-column-count:1">
* <code>hmmdecode</code>
* <code>hmmtrain</code>
</div>
</div>


Line 765: Line 720:
! Description
! Description
|-
|-
| [https://gnu-octave.github.io/statistics/boxplot.html boxplot]
| boxplot
| Produce a box plot.
| Produce a box plot.
|-
|-
| [https://gnu-octave.github.io/statistics/cdfplot.html cdfplot]
| cdfplot
| Display an empirical cumulative distribution function.
| Display an empirical cumulative distribution function.
|-
|-
| [https://gnu-octave.github.io/statistics/confusionchart.html confusionchart]
| confusionchart
| Display a chart of a confusion matrix.
| Display a chart of a confusion matrix.
|-
|-
| [https://gnu-octave.github.io/statistics/dendrogram.html dendrogram]
| dendrogram
| Plot a dendrogram of a hierarchical binary cluster tree.
| Plot a dendrogram of a hierarchical binary cluster tree.
|-
|-
| [https://gnu-octave.github.io/statistics/ecdf.html ecdf]
| ecdf
| Empirical (Kaplan-Meier) cumulative distribution function.
| Empirical (Kaplan-Meier) cumulative distribution function.
|-
|-
| [https://gnu-octave.github.io/statistics/gscatter.html gscatter]
| gscatter
| Draw a scatter plot with grouped data.
| Draw a scatter plot with grouped data.
|-
|-
| [https://gnu-octave.github.io/statistics/histfit.html histfit]
| histfit
| Plot histogram with superimposed fitted normal density.
| Plot histogram with superimposed fitted normal density.
|-
|-
| [https://gnu-octave.github.io/statistics/hist3.html hist3]
| hist3
| Produce bivariate (2D) histogram counts or plots.
| Produce bivariate (2D) histogram counts or plots.
|-
|-
| [https://gnu-octave.github.io/statistics/manovacluster.html manovacluster]
| manovacluster
| Cluster group means using manova1 output.
| Cluster group means using manova1 output.
|-
|-
| [https://gnu-octave.github.io/statistics/normplot.html normplot]
| normplot
| Produce normal probability plot of the data.
| Produce normal probability plot of the data.
|-
|-
| [https://gnu-octave.github.io/statistics/ppplot.html ppplot]
| ppplot
| Perform a PP-plot (probability plot).
| Produce a probability plot.
|-
|-
| [https://gnu-octave.github.io/statistics/qqplot.html qqplot]
| qqplot
| Perform a QQ-plot (quantile plot).
| Produce an empirical quantile-quantile plot.
|-
|-
| [https://gnu-octave.github.io/statistics/silhouette.html silhouette]
| silhouette
| Compute the silhouette values of clustered data and show them on a plot.
| Compute the silhouette values of clustered data and show them on a plot.
|-
|-
| [https://gnu-octave.github.io/statistics/violin.html violin]
| violin
| Produce a Violin plot of the data.
| Produce a Violin plot of the data.
|-
|-
| [https://gnu-octave.github.io/statistics/wblplot.html wblplot]
| wblplot
| Plot a column vector DATA on a Weibull probability plot using rank regression.
| Plot a column vector DATA on a Weibull probability plot using rank regression.
|}
|}
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! Description
! Description
|-
|-
| [https://gnu-octave.github.io/statistics/canoncorr.html canoncorr]
| canoncorr
| Canonical correlation analysis.
| Canonical correlation analysis.
|-
|-
| [https://gnu-octave.github.io/statistics/cholcov.html cholcov]
| cholcov
| Cholesky-like decomposition for covariance matrix.
| Cholesky-like decomposition for covariance matrix.
|-
|-
| [https://gnu-octave.github.io/statistics/dcov.html dcov]
| dcov
| Distance correlation, covariance and correlation statistics.
| Distance correlation, covariance and correlation statistics.
|-
|-
| [https://gnu-octave.github.io/statistics/logistic_regression.html logistic_regression]
| logistic_regression
| Perform ordinal logistic regression.
| Perform ordinal logistic regression.
|-
|-
| [https://gnu-octave.github.io/statistics/monotone_smooth.html monotone_smooth]
| monotone_smooth
| Produce a smooth monotone increasing approximation to a sampled functional dependence.
| Produce a smooth monotone increasing approximation to a sampled functional dependence.
|-
|-
| [https://gnu-octave.github.io/statistics/pca.html pca]
| pca
| Performs a principal component analysis on a data matrix.
| Performs a principal component analysis on a data matrix.
|-
|-
| [https://gnu-octave.github.io/statistics/pcacov.html pcacov]
| pcacov
| Perform principal component analysis on the NxN covariance matrix X
| Perform principal component analysis on the NxN covariance matrix X
|-
|-
| [https://gnu-octave.github.io/statistics/pcares.html pcares]
| pcares
| Calculate residuals from principal component analysis.
| Calculate residuals from principal component analysis.
|-
|-
| [https://gnu-octave.github.io/statistics/plsregress.html plsregress]
| plsregress
| Calculate partial least squares regression using SIMPLS algorithm.
| Calculate partial least squares regression using SIMPLS algorithm.
|-
|-
| [https://gnu-octave.github.io/statistics/princomp.html princomp]
| princomp
| Performs a principal component analysis on a NxP data matrix.
| Performs a principal component analysis on a NxP data matrix.
|-
|-
| [https://gnu-octave.github.io/statistics/regress.html regress]
| regress
| Multiple Linear Regression using Least Squares Fit.
| Multiple Linear Regression using Least Squares Fit.
|-
|-
| [https://gnu-octave.github.io/statistics/regress_gp.html regress_gp]
| regress_gp
| Linear scalar regression using gaussian processes.
| Linear scalar regression using gaussian processes.
|-
|-
| [https://gnu-octave.github.io/statistics/stepwisefit.html stepwisefit]
| stepwisefit
| Linear regression with stepwise variable selection.
| Linear regression with stepwise variable selection.
|}
|}
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== Wrappers ==
== Wrappers ==
=== Available functions ===


Functions available for wrapping other functions or group of functions.
Functions available for wrapping other functions or group of functions.
Line 895: Line 848:
! Description
! Description
|-
|-
| [https://gnu-octave.github.io/statistics/cdf.html cdf]
| cdf
| This is a wrapper for the NAMEcdf and NAME_cdf functions available in the statistics package.
| This is a wrapper around various NAMEcdf and NAME_cdf functions.
|-
| [https://gnu-octave.github.io/statistics/icdf.html icdf]
| This is a wrapper for the NAMEinv and NAME_inv functions available in the statistics package.
|-
|-
| [https://gnu-octave.github.io/statistics/pdf.html pdf]
| pdf
| This is a wrapper for the NAMEpdf and NAME_pdf functions available in the statistics package.
| This is a wrapper around various NAMEpdf and NAME_pdf functions.
|-
|-
| [https://gnu-octave.github.io/statistics/random.html random]
| random
| Generates pseudo-random numbers from a given one-, two-, or three-parameter distribution.
| Generates pseudo-random numbers from a given one-, two-, or three-parameter distribution.
|}
|}
=== TODO list ===
Update <code>cdf</code>, <code>pdf</code>, and <code>random</code> to include the latest changes in distribution functions available in statistics-1.5.3.
Missing functions:
<div style="column-count:1;-moz-column-count:1;-webkit-column-count:1">
* <code>icdf</code>
</div>


[[Category:Packages]]
[[Category:Packages]]
[[Category:Missing functions]]
[[Category:Missing functions]]
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