Statistics package

Revision as of 23:32, 4 February 2023 by Pr0m1th3as (talk | contribs)

The statistics package is part of the Octave Packages. Since version 1.5.0, the statistics package requires Octave version 6.1 or higher. From Octave v7.2 or later, you can install the latest statistics package (currently 1.5.3) with the following command:

pkg install -forge statistics

Clustering

Data Manipulation

Descriptive Statistics

Available functions

The following table lists the functions available for descriptive statistics.

Function Description
geomean Compute the geometric mean.
grpstats Compute summary statistics by group. Fully MATLAB compatible.
harmmean Compute the harmonic mean.
jackknife Compute jackknife estimates of a parameter taking one or more given samples as parameters.
mean Compute the mean. Fully MATLAB compatible.
median Compute the median. Fully MATLAB compatible.
nanmax Find the maximal element while ignoring NaN values.
nanmin Find the minimal element while ignoring NaN values.
nansum Compute the sum while ignoring NaN values.
std Compute the standard deviation. Fully MATLAB compatible.
trimmean Compute the trimmed mean.
std Compute the variance. Fully MATLAB compatible.

In external packages

bootci, bootstrp are implemented in the statistics-bootstrap package.

Shadowing Octave core functions

The following functions will shadow the respective core functions until Octave 9.

  • mean
  • median
  • std
  • var

Distributions

Available functions

The following table lists the cdf, icdf, pdf, and random functions available in the statistics package. Since version 1.5.3, all CDFs support the "upper" option for evaluating the complement of the respective CDF.

Note! The icdf wrapper for the quantile functions is not implemented yet.

Distribution Name Cumulative Distribution Function Quantile Function Probability Density Function Random Generator
Birnbaum–Saunders bbscdf bbsinv bbspdf bbsrnd
Beta betacdf betainv betapdf betarndbivariate
[Binomial binocdf binoinv binopdf binornd
Bivariate bvncdf
Burr Type XII burrcdf burrinv burrpdf burrrnd
Cauchy cauchy_cdf cauchy_inv cauchy_pdf cauchy_rnd
Chi-squared chi2cdf chi2inv chi2pdf chi2rnd
Copula Family copulacdf copulainv copulapdf copularnd
Extreme Value evcdf evinv evpdf evrnd
Exponential expcdf expinv exppdf exprnd
F fcdf finv fpdf frnd
Gamma gamcdf gaminv gampdf gamrnd
Geometric geocdf geoinv geopdf geornd
Generalized Extreme Value gevcdf gevinv gevpdf gevrnd
Generalized Pareto gpcdf gpinv gppdf gprnd
Hypergeometric hygecdf hygeinv hygepdf hygernd
Inverse-Wishart iwishpdf iwishrnd
Johnson's SU jsucdf jsupdf
Laplace laplace_cdf laplace_inv laplace_pdf laplace_rnd
Logistic logistic_cdf logistic_inv logistic_pdf logistic_rnd
Log-normal logncdf logninv lognpdf lognrnd
Multinomial mnpdf mnrnd
Multivariate Normal mvncdf mvninv mvnpdf mvnrnd
Multivariate Student's T mvtcdf mvtcdfqmc mvtinv mvtpdf mvtrnd
Nakagami nakacdf nakainv nakapdf nakarnd
Negative Binomial nbincdf nbininv nbinpdf nbinrnd
Noncentral F ncfcdf ncfinv ncfpdf ncfrnd
Noncentral Student's T nctcdf nctinv nctpdf nctrnd
Noncentral Chi-squared ncx2cdf ncx2inv ncx2pdf ncx2rnd
Normal normcdf norminv normpdf normrnd
Poisson poisscdf poissinv poisspdf poissrnd
Rayleigh raylcdf raylinv raylpdf raylrnd
Standard Normal stdnormal_cdf stdnormal_inv stdnormal_pdf stdnormal_rnd
Student's T tcdf tinv tpdf trnd
Triangular tricdf triinv tripdf trirnd
Discrete Uniform unidcdf unidinv unidpdf unidrnd
Continuous Uniform unifcdf unifinv unifpdf unifrnd
von Mises vmcdf vmpdf vmrnd
Weibull wblcdf wblinv wblpdf wblrnd
Wiener process wienrnd
Wishart wishpdf wishrnd


Distribution Fitting

Functions available for estimating parameters and the negative log-likelihood for certain distributions.

Distribution Name Parameter Estimation Negativel Log-likelihood
Extreme Value evfit evlike
Exponential expfit explike
Gamma gamfit gamlike
Generalized Extreme Value gevfit_lmom gevfit gevlike
Generalized Pareto gpfit gplike
Normal normlike

Distribution Statistics

Functions available for computing mean and variance from distribution parameters.

  • betastat
  • binostat
  • chi2stat
  • evstat
  • expstat
  • fstat
  • gamstat
  • geostat
  • gevstat
  • gpstat
  • hygestat
  • lognstat
  • nbinstat
  • ncfstat
  • nctstat
  • ncx2stat
  • normstat
  • poisstat
  • raylstat
  • fitgmdist
  • tstat
  • unidstat
  • unifstat
  • wblstat

Experimental Design

Functions available for computing design matrices.

  • fullfact
  • ff2n
  • x2fx

Model Fitting

  • crossval
  • fitgmdist
  • fitlm

Cross Validation

Class of set partitions for cross-validation, used in crossval

  • @cvpartition/cvpartition
  • @cvpartition/display
  • @cvpartition/get
  • @cvpartition/repartition
  • @cvpartition/set
  • @cvpartition/test
  • @cvpartition/training

Missing options

  • explike: censoring and frequency aren't yet implemented