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<code>pkg install -forge statistics</code> | <code>pkg install -forge statistics</code> | ||
== Clustering == | == Clustering == | ||
== Data Manipulation == | == Data Manipulation == | ||
== Descriptive Statistics == | == Descriptive Statistics == | ||
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=== Available functions === | === Available functions === | ||
The following table lists the available | The following table lists the functions available for descriptive statistics. | ||
{| class="wikitable" | {| class="wikitable" | ||
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! Description | ! Description | ||
|- | |- | ||
| | | geomean | ||
| Compute the geometric mean. | | Compute the geometric mean. | ||
|- | |- | ||
| | | grpstats | ||
| Compute summary statistics by group. Fully MATLAB compatible. | | Compute summary statistics by group. Fully MATLAB compatible. | ||
|- | |- | ||
| | | harmmean | ||
| Compute the harmonic mean. | | Compute the harmonic mean. | ||
|- | |- | ||
| | | 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. | ||
|- | |- | ||
| | | mean | ||
| Compute the mean. Fully MATLAB compatible. | | Compute the mean. Fully MATLAB compatible. | ||
|- | |- | ||
| | | median | ||
| Compute the median. Fully MATLAB compatible. | | Compute the median. Fully MATLAB compatible. | ||
|- | |- | ||
| | | nanmax | ||
| Find the maximal element while ignoring NaN values. | | Find the maximal element while ignoring NaN values. | ||
|- | |- | ||
| | | nanmin | ||
| Find the minimal element while ignoring NaN values. | | Find the minimal element while ignoring NaN values. | ||
|- | |- | ||
| | | nansum | ||
| Compute the sum while ignoring NaN values. | | Compute the sum while ignoring NaN values. | ||
|- | |- | ||
| | | std | ||
| Compute the standard deviation. Fully MATLAB compatible. | | Compute the standard deviation. Fully MATLAB compatible. | ||
|- | |- | ||
| | | trimmean | ||
| Compute the trimmed mean. | | Compute the trimmed mean. | ||
|- | |- | ||
| | | std | ||
| Compute the variance. Fully MATLAB compatible. | | Compute the variance. Fully MATLAB compatible. | ||
|} | |} | ||
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=== In external packages === | === In external packages === | ||
bootci, bootstrp 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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<div style="column-count:1;-moz-column-count:1;-webkit-column-count:1"> | <div style="column-count:1;-moz-column-count:1;-webkit-column-count:1"> | ||
* | * mean | ||
* | * median | ||
* | * std | ||
* | * var | ||
</div> | </div> | ||
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| binornd | | binornd | ||
|- | |- | ||
| | | Bivariate | ||
| bvncdf | | bvncdf | ||
| | | | ||
| | | | ||
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| chi2rnd | | chi2rnd | ||
|- | |- | ||
| | | Copula Family | ||
| copulacdf | | copulacdf | ||
| copulainv | | copulainv | ||
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| copularnd | | copularnd | ||
|- | |- | ||
| | | Extreme Value | ||
| evcdf | | evcdf | ||
| evinv | | evinv | ||
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| mvnrnd | | mvnrnd | ||
|- | |- | ||
| [https://en.wikipedia.org/wiki/Multivariate_t-distribution Multivariate Student's | | [https://en.wikipedia.org/wiki/Multivariate_t-distribution Multivariate Student's T] | ||
| mvtcdf mvtcdfqmc | | mvtcdf mvtcdfqmc | ||
| mvtinv | | mvtinv | ||
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| ncfrnd | | ncfrnd | ||
|- | |- | ||
| [https://en.wikipedia.org/wiki/Noncentral_t-distribution Noncentral Student's | | [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 | | [https://en.wikipedia.org/wiki/Student%27s_t-distribution Student's T] | ||
| tcdf | | tcdf | ||
| tinv | | tinv | ||
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| wishrnd | | wishrnd | ||
|} | |} | ||
=== Distribution Fitting === | === Distribution Fitting === | ||
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<div style="column-count:4;-moz-column-count:4;-webkit-column-count:4"> | <div style="column-count:4;-moz-column-count:4;-webkit-column-count:4"> | ||
* | * betastat | ||
* | * binostat | ||
* | * chi2stat | ||
* | * evstat | ||
* | * expstat | ||
* | * fstat | ||
* | * gamstat | ||
* | * geostat | ||
* | * gevstat | ||
* | * gpstat | ||
* | * hygestat | ||
* | * lognstat | ||
* | * nbinstat | ||
* | * ncfstat | ||
* | * nctstat | ||
* | * ncx2stat | ||
* | * normstat | ||
* | * poisstat | ||
* | * raylstat | ||
* | * fitgmdist | ||
* | * tstat | ||
* | * unidstat | ||
* | * unifstat | ||
* | * wblstat | ||
</div> | </div> | ||
== Experimental Design == | == Experimental Design == | ||
Functions available for computing design matrices. | Functions available for computing design matrices. | ||
<div style="column-count:1;-moz-column-count:1;-webkit-column-count:1"> | <div style="column-count:1;-moz-column-count:1;-webkit-column-count:1"> | ||
* | * fullfact | ||
* | * ff2n | ||
* x2fx | |||
</div> | </div> | ||
== Model Fitting == | == Model Fitting == | ||
Functions available for computing design matrices. | |||
<div style="column-count:1;-moz-column-count:1;-webkit-column-count:1"> | |||
* crossval | |||
* fitgmdist | |||
* fitlm | |||
</div> | |||
=== Cross Validation === | === Cross Validation === | ||
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* @cvpartition/test | * @cvpartition/test | ||
* @cvpartition/training | * @cvpartition/training | ||
</div> | </div> | ||
== Hypothesis Testing == | == Hypothesis Testing == | ||
Functions available for hypothesis testing | Functions available for hypothesis testing | ||
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! Description | ! Description | ||
|- | |- | ||
| | | adtest | ||
| Anderson-Darling goodness-of-fit hypothesis test. | | Anderson-Darling goodness-of-fit hypothesis test. | ||
|- | |- | ||
| | | anova1 | ||
| Perform a one-way analysis of variance (ANOVA) | | Perform a one-way analysis of variance (ANOVA) | ||
|- | |- | ||
| | | 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 | ||
| 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 | ||
| Perform a Bartlett test for the homogeneity of variances. | | Perform a Bartlett test for the homogeneity of variances. | ||
|- | |- | ||
| | | barttest | ||
| Bartlett's test of sphericity for correlation. | | Bartlett's test of sphericity for correlation. | ||
|- | |- | ||
| | | binotest | ||
| Test for probability P of a binomial sample | | Test for probability P of a binomial sample | ||
|- | |- | ||
| | | chi2gof | ||
| Chi-square goodness-of-fit test. | | Chi-square goodness-of-fit test. | ||
|- | |- | ||
| | | chi2test | ||
| Perform a chi-squared test (for independence or homogeneity). | | Perform a chi-squared test (for independence or homogeneity). | ||
|- | |- | ||
| | | 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 | ||
| 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 | ||
| 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 | ||
| 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 | ||
| Single sample Kolmogorov-Smirnov (K-S) goodness-of-fit hypothesis test. | | Single sample Kolmogorov-Smirnov (K-S) goodness-of-fit hypothesis test. | ||
|- | |- | ||
| | | kstest2 | ||
| Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test. | | Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test. | ||
|- | |- | ||
| | | levene_test | ||
| Perform a Levene's test for the homogeneity of variances. | | Perform a Levene's test for the homogeneity of variances. | ||
|- | |- | ||
| | | manova1 | ||
| One-way multivariate analysis of variance (MANOVA). | | One-way multivariate analysis of variance (MANOVA). | ||
|- | |- | ||
| | | 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 | ||
| F-test for General Linear Regression Analysis | | F-test for General Linear Regression Analysis | ||
|- | |- | ||
| | | 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''. | ||
|- | |- | ||
| | | runstest | ||
| Runs test for detecting serial correlation in the vector X. | | Runs test for detecting serial correlation in the vector X. | ||
|- | |- | ||
| | | sampsizepwr | ||
| Sample size and power calculation for hypothesis test. | | Sample size and power calculation for hypothesis test. | ||
|- | |- | ||
| | | signtest | ||
| Test for median. | | Test for median. | ||
|- | |- | ||
| | | 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 | ||
| Perform a two independent samples t-test. | | Perform a two independent samples t-test. | ||
|- | |- | ||
| | | vartest | ||
| One-sample test of variance. | | One-sample test of variance. | ||
|- | |- | ||
| | | vartest2 | ||
| Two-sample F test for equal variances. | | Two-sample F test for equal variances. | ||
|- | |- | ||
| | | vartestn | ||
| Test for equal variances across multiple groups. | | Test for equal variances across multiple groups. | ||
|- | |- | ||
| | | ztest | ||
| One-sample Z-test. | | One-sample Z-test. | ||
|} | |} | ||
[[Category: | [[Category:Octave Forge]] | ||
[[Category:Missing functions]] | [[Category:Missing functions]] |