Statistics package: Difference between revisions
Pr0m1th3as (talk | contribs) Tags: Mobile edit Mobile web edit Advanced mobile edit |
Pr0m1th3as (talk | contribs) Tags: Mobile edit Mobile web edit Advanced mobile edit |
||
Line 91: | Line 91: | ||
| Randomly sample data. | | Randomly sample data. | ||
|- | |- | ||
| https://gnu-octave.github.io/statistics/grp2idx.html grp2idx] | | [https://gnu-octave.github.io/statistics/fillmissing.html fillmissing] | ||
| 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] | ||
Line 860: | Line 875: | ||
|- | |- | ||
| [https://gnu-octave.github.io/statistics/cdf.html cdf] | | [https://gnu-octave.github.io/statistics/cdf.html cdf] | ||
| This is a wrapper | | This is a wrapper for the NAMEcdf and NAME_cdf functions available in the statistics package. | ||
|- | |||
| [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] | | [https://gnu-octave.github.io/statistics/pdf.html pdf] | ||
| This is a wrapper | | This is a wrapper for the NAMEpdf and NAME_pdf functions available in the statistics package. | ||
|- | |- | ||
| [https://gnu-octave.github.io/statistics/random.html 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. | ||
|} | |} | ||
[[Category:Packages]] | [[Category:Packages]] | ||
[[Category:Missing functions]] | [[Category:Missing functions]] |
Revision as of 14:12, 21 February 2023
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
The following sections provide an overview of the functions available in the statistics package sorted alphabetically and arranged in groups similarly to the package's INDEX file. the TODO subsections are only informative of the current development plans for the forthcoming releases and they are not intended for reporting bugs, missing features or incompatibilities. Please report these in the statistics repository at GitHub.
Clustering
Available functions
The following table lists the available functions for clustering data.
Function | Description |
---|---|
cluster | Define clusters from an agglomerative hierarchical cluster tree. |
clusterdata | Wrapper function for 'linkage' and 'cluster'. |
cmdscale | Classical multidimensional scaling of a matrix. |
confusionmat | Compute a confusion matrix for classification problems. |
cophenet | Compute the cophenetic correlation coefficient. |
evalclusters | Create a clustering evaluation object to find the optimal number of clusters. |
inconsistent | Compute the inconsistency coefficient for each link of a hierarchical cluster tree. |
kmeans | Perform a K-means clustering of an NxD matrix. |
linkage | Produce a hierarchical clustering dendrogram. |
mahal | Mahalanobis' D-square distance. |
mhsample | Draws NSAMPLES samples from a target stationary distribution PDF using Metropolis-Hastings algorithm. |
optimalleaforder | Compute the optimal leaf ordering of a hierarchical binary cluster tree. |
pdist | Return the distance between any two rows in X. |
pdist2 | Compute pairwise distance between two sets of vectors. |
slicesample | Draws NSAMPLES samples from a target stationary distribution PDF using slice sampling of Radford M. Neal. |
squareform | Interchange between distance matrix and distance vector formats. |
TODO list
Missing functions:
procrustes
Data Manipulation
Available functions
The following table lists the available functions for data manipulation.
Function | Description |
---|---|
combnk | Return all combinations of K elements in DATA. |
crosstab | Create a cross-tabulation (contingency table) T from data vectors. |
datasample | Randomly sample data. |
fillmissing | Replace missing entries of array A either with values in v or as determined by other specified methods. |
grp2idx | Get index for group variables. |
ismissing | Find missing data in a numeric or string array. |
normalise_distribution | Transform a set of data so as to be N(0,1) distributed according to an idea by van Albada and Robinson. |
rmmissing | Remove missing or incomplete data from an array. |
standardizeMissing | Replace data values specified by indicator in A by the standard ’missing’ data value for that data type. |
tabulate | Compute a frequency table. |
Descriptive Statistics
Available functions
The following table lists the available functions 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
TODO list
Update trimmean
function to be fully MATLAB compatible.
Re-introduce the nan*
functions implemented in C++ with the "all"
and "vecdim"
options.
Re-implement the following functions from core Octave, as shadowing functions with updated functionality regarding the "all"
, "omitnan"
, and "vecdim"
options, with the intend to be included in Octave 9.
cov
mad
meansq
mode
moment
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
Available functions
Functions available for computing design matrices.
Function | Description |
---|---|
fullfact | Full factorial design. |
ff2n | Two-level full factorial design. |
sigma_pts | Calculates 2*N+1 sigma points in N dimensions. |
x2fx | Convert predictors to design matrix. |
Machine Learning
Available functions
The following table lists the available functions.
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 svmpredict
and svmtrain
to libsvm 3.0.
Missing functions:
hmmdecode
hmmtrain
Model Fitting
Available functions
Functions available for fitting or evaluating statistical models.
Function | Description |
---|---|
crossval | Perform cross validation on given data. |
fitgmdist | Fit a Gaussian mixture model with K components to DATA. |
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. |
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
TODO list
Missing functions:
anova
manova
Hypothesis Testing
Available functions
Functions available for hypothesis testing
Function | Description |
---|---|
adtest | Anderson-Darling goodness-of-fit hypothesis test. |
anova1 | Perform a one-way analysis of variance (ANOVA) |
anova2 | 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). |
bartlett_test | Perform a Bartlett test for the homogeneity of variances. |
barttest | Bartlett's test of sphericity for correlation. |
binotest | Test for probability P of a binomial sample |
chi2gof | Chi-square goodness-of-fit test. |
chi2test | 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. |
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). |
hotelling_t2test2 | 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). |
kstest | Single sample Kolmogorov-Smirnov (K-S) goodness-of-fit hypothesis test. |
kstest2 | Two-sample Kolmogorov-Smirnov goodness-of-fit hypothesis test. |
levene_test | Perform a Levene's test for the homogeneity of variances. |
manova1 | One-way multivariate analysis of variance (MANOVA). |
multcompare | Perform posthoc multiple comparison tests or p-value adjustments to control the family-wise error rate (FWER) or false discovery rate (FDR). |
ranksum | 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 |
regression_ttest | Perform a linear regression t-test. |
runstest | Runs test for detecting serial correlation in the vector X. |
sampsizepwr | Sample size and power calculation for hypothesis test. |
signtest | Test for median. |
ttest | Test for mean of a normal sample with unknown variance or a paired-sample t-test. |
ttest2 | Perform a two independent samples t-test. |
vartest | One-sample test of variance. |
vartest2 | Two-sample F test for equal variances. |
vartestn | Test for equal variances across multiple groups. |
ztest | One-sample Z-test. |
ztest2 | Two proportions Z-test. |
TODO list
Missing functions:
fishertest
meanEffectSize
Plotting
Available functions
The following table lists the available functions for plotting data.
Function | Description |
---|---|
boxplot | Produce a box plot. |
cdfplot | Display an empirical cumulative distribution function. |
confusionchart | Display a chart of a confusion matrix. |
dendrogram | Plot a dendrogram of a hierarchical binary cluster tree. |
ecdf | Empirical (Kaplan-Meier) cumulative distribution function. |
gscatter | Draw a scatter plot with grouped data. |
histfit | Plot histogram with superimposed fitted normal density. |
hist3 | Produce bivariate (2D) histogram counts or plots. |
manovacluster | Cluster group means using manova1 output. |
normplot | Produce normal probability plot of the data. |
ppplot | Perform a PP-plot (probability plot). |
qqplot | Perform a QQ-plot (quantile plot). |
silhouette | Compute the silhouette values of clustered data and show them on a plot. |
violin | Produce a Violin plot of the data. |
wblplot | Plot a column vector DATA on a Weibull probability plot using rank regression. |
TODO list
Missing functions:
andrewsplot
bar3
bar3h
glyphplot
gplotmatrix
parallelcoords
Regression
Available functions
The following table lists the available functions for regression analysis.
Function | Description |
---|---|
canoncorr | Canonical correlation analysis. |
cholcov | Cholesky-like decomposition for covariance matrix. |
dcov | Distance correlation, covariance and correlation statistics. |
logistic_regression | Perform ordinal logistic regression. |
monotone_smooth | Produce a smooth monotone increasing approximation to a sampled functional dependence. |
pca | Performs a principal component analysis on a data matrix. |
pcacov | Perform principal component analysis on the NxN covariance matrix X |
pcares | Calculate residuals from principal component analysis. |
plsregress | Calculate partial least squares regression using SIMPLS algorithm. |
princomp | Performs a principal component analysis on a NxP data matrix. |
regress | Multiple Linear Regression using Least Squares Fit. |
regress_gp | Linear scalar regression using gaussian processes. |
stepwisefit | Linear regression with stepwise variable selection. |
TODO list
Missing functions:
glmfit
glmval
mnrfit
mnrval
Wrappers
Available functions
Functions available for wrapping other functions or group of functions.
Function | Description |
---|---|
cdf | This is a wrapper for the NAMEcdf and NAME_cdf functions available in the statistics package. |
icdf | This is a wrapper for the NAMEinv and NAME_inv functions available in the statistics package. |
This is a wrapper for the NAMEpdf and NAME_pdf functions available in the statistics package. | |
random | Generates pseudo-random numbers from a given one-, two-, or three-parameter distribution. |