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Statistics package (edit)

Revision as of 15:34, 20 February 2023

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| 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 ==
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! Description
! Description
|-
|-
| adtest
| [https://gnu-octave.github.io/statistics/adtest.html adtest]
| Anderson-Darling goodness-of-fit hypothesis test.
| Anderson-Darling goodness-of-fit hypothesis test.
|-
|-
| anova1
| [https://gnu-octave.github.io/statistics/anova1.html anova1]
| Perform a one-way analysis of variance (ANOVA)
| Perform a one-way analysis of variance (ANOVA)
|-
|-
| anova2
| [https://gnu-octave.github.io/statistics/anova2.html 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.
|-
|-
| anovan
| [https://gnu-octave.github.io/statistics/anovan.html 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).
|-
|-
| bartlett_test
| [https://gnu-octave.github.io/statistics/bartlett_test.html bartlett_test]
| Perform a Bartlett test for the homogeneity of variances.
| Perform a Bartlett test for the homogeneity of variances.
|-
|-
| barttest
| [https://gnu-octave.github.io/statistics/barttest.html barttest]
| Bartlett's test of sphericity for correlation.
| Bartlett's test of sphericity for correlation.
|-
|-
| binotest
| [https://gnu-octave.github.io/statistics/binotest.html binotest]
| Test for probability P of a binomial sample
| Test for probability P of a binomial sample
|-
|-
| chi2gof
| [https://gnu-octave.github.io/statistics/chi2gof.html chi2gof]
| Chi-square goodness-of-fit test.
| Chi-square goodness-of-fit test.
|-
|-
| chi2test
| [https://gnu-octave.github.io/statistics/chi2test.html chi2test]
| Perform a chi-squared test (for independence or homogeneity).
| Perform a chi-squared test (for independence or homogeneity).
|-
|-
| friedman
| [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.
|-
|-
| hotelling_t2test
| https://gnu-octave.github.io/statistics/hotelling_t2test.html 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).
|-
|-
| hotelling_t2test2
| [https://gnu-octave.github.io/statistics/hotelling_t2test2.html 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.
|-
|-
| kruskalwallis
| [https://gnu-octave.github.io/statistics/kruskalwallis.html 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).
|-
|-
| kstest
| [https://gnu-octave.github.io/statistics/kstest.html kstest]
| Single sample Kolmogorov-Smirnov (K-S) goodness-of-fit hypothesis test.
| Single sample Kolmogorov-Smirnov (K-S) goodness-of-fit hypothesis test.
|-
|-
| kstest2
| [https://gnu-octave.github.io/statistics/kstest2.html kstest2]
| Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test.
| Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test.
|-
|-
| levene_test
| [https://gnu-octave.github.io/statistics/levene_test.html levene_test]
| Perform a Levene's test for the homogeneity of variances.
| Perform a Levene's test for the homogeneity of variances.
|-
|-
| manova1
| [https://gnu-octave.github.io/statistics/manova1.html manova1]
| One-way multivariate analysis of variance (MANOVA).
| One-way multivariate analysis of variance (MANOVA).
|-
|-
| multcompare
| [https://gnu-octave.github.io/statistics/multcompare.html 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).
|-
|-
| ranksum
| [https://gnu-octave.github.io/statistics/ranksum.html 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.
|-
|-
| regression_ftest
| [https://gnu-octave.github.io/statistics/regression_ftest.html regression_ftest]
| F-test for General Linear Regression Analysis
| F-test for General Linear Regression Analysis
|-
|-
| regression_ttest
| [https://gnu-octave.github.io/statistics/regression_ttest.html regression_ttest]
| Perform a linear regression t-test for the null hypothesis ''RR * B = R'' in a classical normal regression model ''Y = X * B + E''.
| Perform a linear regression t-test.
|-
|-
| runstest
| [https://gnu-octave.github.io/statistics/runstest.html runstest]
| Runs test for detecting serial correlation in the vector X.
| Runs test for detecting serial correlation in the vector X.
|-
|-
| sampsizepwr
| [https://gnu-octave.github.io/statistics/sampsizepwr.html sampsizepwr]
| Sample size and power calculation for hypothesis test.
| Sample size and power calculation for hypothesis test.
|-
|-
| signtest
| [https://gnu-octave.github.io/statistics/signtest.html signtest]
| Test for median.
| Test for median.
|-
|-
| ttest
| [https://gnu-octave.github.io/statistics/ttest.html 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.
|-
|-
| ttest2
| [https://gnu-octave.github.io/statistics/ttest2.html ttest2]
| Perform a two independent samples t-test.
| Perform a two independent samples t-test.
|-
|-
| vartest
| [https://gnu-octave.github.io/statistics/vartest.html vartest]
| One-sample test of variance.
| One-sample test of variance.
|-
|-
| vartest2
| [https://gnu-octave.github.io/statistics/vartest2.html vartest2]
| Two-sample F test for equal variances.
| Two-sample F test for equal variances.
|-
|-
| vartestn
| [https://gnu-octave.github.io/statistics/vartestn.html vartestn]
| Test for equal variances across multiple groups.
| Test for equal variances across multiple groups.
|-
|-
| ztest
| [https://gnu-octave.github.io/statistics/ztest.html 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>


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! Description
! Description
|-
|-
| boxplot
| [https://gnu-octave.github.io/statistics/boxplot.html boxplot]
| Produce a box plot.
| Produce a box plot.
|-
|-
| cdfplot
| [https://gnu-octave.github.io/statistics/cdfplot.html cdfplot]
| Display an empirical cumulative distribution function.
| Display an empirical cumulative distribution function.
|-
|-
| confusionchart
| [https://gnu-octave.github.io/statistics/confusionchart.html confusionchart]
| Display a chart of a confusion matrix.
| Display a chart of a confusion matrix.
|-
|-
| dendrogram
| [https://gnu-octave.github.io/statistics/dendrogram.html dendrogram]
| Plot a dendrogram of a hierarchical binary cluster tree.
| Plot a dendrogram of a hierarchical binary cluster tree.
|-
|-
| ecdf
| [https://gnu-octave.github.io/statistics/ecdf.html ecdf]
| Empirical (Kaplan-Meier) cumulative distribution function.
| Empirical (Kaplan-Meier) cumulative distribution function.
|-
|-
| gscatter
| [https://gnu-octave.github.io/statistics/gscatter.html gscatter]
| Draw a scatter plot with grouped data.
| Draw a scatter plot with grouped data.
|-
|-
| histfit
| [https://gnu-octave.github.io/statistics/histfit.html histfit]
| Plot histogram with superimposed fitted normal density.
| Plot histogram with superimposed fitted normal density.
|-
|-
| hist3
| [https://gnu-octave.github.io/statistics/hist3.html hist3]
| Produce bivariate (2D) histogram counts or plots.
| Produce bivariate (2D) histogram counts or plots.
|-
|-
| manovacluster
| [https://gnu-octave.github.io/statistics/manovacluster.html manovacluster]
| Cluster group means using manova1 output.
| Cluster group means using manova1 output.
|-
|-
| normplot
| [https://gnu-octave.github.io/statistics/normplot.html normplot]
| Produce normal probability plot of the data.
| Produce normal probability plot of the data.
|-
|-
| ppplot
| [https://gnu-octave.github.io/statistics/ppplot.html ppplot]
| Produce a probability plot.
| Perform a PP-plot (probability plot).
|-
|-
| qqplot
| [https://gnu-octave.github.io/statistics/qqplot.html qqplot]
| Produce an empirical quantile-quantile plot.
| Perform a QQ-plot (quantile plot).
|-
|-
| silhouette
| [https://gnu-octave.github.io/statistics/silhouette.html 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.
|-
|-
| violin
| [https://gnu-octave.github.io/statistics/violin.html violin]
| Produce a Violin plot of the data.
| Produce a Violin plot of the data.
|-
|-
| wblplot
| [https://gnu-octave.github.io/statistics/wblplot.html 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.
|}
|}
Line 789: Line 792:
! Description
! Description
|-
|-
| canoncorr
| [https://gnu-octave.github.io/statistics/canoncorr.html canoncorr]
| Canonical correlation analysis.
| Canonical correlation analysis.
|-
|-
| cholcov
| [https://gnu-octave.github.io/statistics/cholcov.html cholcov]
| Cholesky-like decomposition for covariance matrix.
| Cholesky-like decomposition for covariance matrix.
|-
|-
| dcov
| [https://gnu-octave.github.io/statistics/dcov.html dcov]
| Distance correlation, covariance and correlation statistics.
| Distance correlation, covariance and correlation statistics.
|-
|-
| logistic_regression
| [https://gnu-octave.github.io/statistics/logistic_regression.html logistic_regression]
| Perform ordinal logistic regression.
| Perform ordinal logistic regression.
|-
|-
| monotone_smooth
| [https://gnu-octave.github.io/statistics/monotone_smooth.html monotone_smooth]
| Produce a smooth monotone increasing approximation to a sampled functional dependence.
| Produce a smooth monotone increasing approximation to a sampled functional dependence.
|-
|-
| pca
| [https://gnu-octave.github.io/statistics/pca.html pca]
| Performs a principal component analysis on a data matrix.
| Performs a principal component analysis on a data matrix.
|-
|-
| pcacov
| [https://gnu-octave.github.io/statistics/pcacov.html pcacov]
| Perform principal component analysis on the NxN covariance matrix X
| Perform principal component analysis on the NxN covariance matrix X
|-
|-
| pcares
| [https://gnu-octave.github.io/statistics/pcares.html pcares]
| Calculate residuals from principal component analysis.
| Calculate residuals from principal component analysis.
|-
|-
| plsregress
| [https://gnu-octave.github.io/statistics/plsregress.html plsregress]
| Calculate partial least squares regression using SIMPLS algorithm.
| Calculate partial least squares regression using SIMPLS algorithm.
|-
|-
| princomp
| [https://gnu-octave.github.io/statistics/princomp.html princomp]
| Performs a principal component analysis on a NxP data matrix.
| Performs a principal component analysis on a NxP data matrix.
|-
|-
| regress
| [https://gnu-octave.github.io/statistics/regress.html regress]
| Multiple Linear Regression using Least Squares Fit.
| Multiple Linear Regression using Least Squares Fit.
|-
|-
| regress_gp
| [https://gnu-octave.github.io/statistics/regress_gp.html regress_gp]
| Linear scalar regression using gaussian processes.
| Linear scalar regression using gaussian processes.
|-
|-
| stepwisefit
| [https://gnu-octave.github.io/statistics/stepwisefit.html stepwisefit]
| Linear regression with stepwise variable selection.
| Linear regression with stepwise variable selection.
|}
|}
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! Description
! Description
|-
|-
| cdf
| [https://gnu-octave.github.io/statistics/cdf.html cdf]
| This is a wrapper around various NAMEcdf and NAME_cdf functions.
| This is a wrapper around various NAMEcdf and NAME_cdf functions.
|-
|-
| pdf
| [https://gnu-octave.github.io/statistics/pdf.html pdf]
| This is a wrapper around various NAMEpdf and NAME_pdf functions.
| This is a wrapper around various NAMEpdf and NAME_pdf functions.
|-
|-
| random
| [https://gnu-octave.github.io/statistics/random.html 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.
|}
|}
Pr0m1th3as
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