statistics

Additional statistics functions for Octave.

Select category:

Distributions

anderson_darling_cdf
Return the CDF for the given Anderson-Darling coefficient A computed from N values sampled from a distribution.
bbscdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Birnbaum-Saunders distribution with parameters LOCATION, SCALE and SHAPE.
bbsinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the Birnbaum-Saunders distribution with parameters LOCATION, SCALE, and SHAPE.
bbspdf
For each element of X, compute the probability density function (PDF) at X of the Birnbaum-Saunders distribution with parameters LOCATION, SCALE and SHAPE.
bbsrnd
Return a matrix of random samples from the Birnbaum-Saunders distribution with parameters LOCATION, SCALE and SHAPE.
betastat
Compute mean and variance of the beta distribution.
binostat
Compute mean and variance of the binomial distribution.
binotest
Test for probability P of a binomial sample
burrcdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Burr distribution with scale parameter ALPHA and shape parameters C and K.
burrinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the Burr distribution with scale parameter ALPHA and shape parameters C and K.
burrpdf
For each element of X, compute the probability density function (PDF) at X of the Burr distribution with scale parameter ALPHA and shape parameters C and K.
burrrnd
Return a matrix of random samples from the generalized Pareto distribution with scale parameter ALPHA and shape parameters C and K.
cdf
Return cumulative density function of NAME function for value X.
chi2stat
Compute mean and variance of the chi-square distribution.
cl_multinom
Returns confidence level of multinomial parameters estimated p = x / sum(x) with predefined confidence interval B.
copulacdf
Compute the cumulative distribution function of a copula family.
copulapdf
Compute the probability density function of a copula family.
copularnd
Generate random samples from a copula family.
datasample
Randomly sample data.
expfit
Estimate the mean of the exponential probability distribution function from which sample data S has been taken.
explike
Compute the negative log-likelihood of data under the exponential distribution with given parameter value.
expstat
Compute mean and variance of the exponential distribution.
fstat
Compute mean and variance of the F distribution.
gamlike
Calculates the negative log-likelihood function for the Gamma distribution over vector R, with the given parameters A and B.
gamstat
Compute mean and variance of the gamma distribution.
geostat
Compute mean and variance of the geometric distribution.
gevcdf
Compute the cumulative distribution function of the generalized extreme value (GEV) distribution.
gevfit
Find the maximum likelihood estimator (PARAMHAT) of the generalized extreme value (GEV) distribution to fit DATA.
gevfit_lmom
Find an estimator (PARAMHAT) of the generalized extreme value (GEV) distribution fitting DATA using the method of L-moments.
gevinv
Compute a desired quantile (inverse CDF) of the generalized extreme value (GEV) distribution.
gevlike
Compute the negative log-likelihood of data under the generalized extreme value (GEV) distribution with given parameter values.
gevpdf
Compute the probability density function of the generalized extreme value (GEV) distribution.
gevrnd
Return a matrix of random samples from the generalized extreme value (GEV) distribution with parameters K, SIGMA, MU.
gevstat
Compute the mean and variance of the generalized extreme value (GEV) distribution.
gmdistribution
Create an object of the gmdistribution class which represents a Gaussian mixture model with k components of n-dimensional Gaussians.
gpcdf
Compute the cumulative distribution function (CDF) at X of the generalized Pareto distribution with parameters LOCATION, SCALE, and SHAPE.
gpinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the generalized Pareto distribution with parameters LOCATION, SCALE, and SHAPE.
gppdf
Compute the probability density function (PDF) at X of the generalized Pareto distribution with parameters LOCATION, SCALE, and SHAPE.
gprnd
Return a matrix of random samples from the generalized Pareto distribution with parameters LOCATION, SCALE and SHAPE.
hygestat
Compute mean and variance of the hypergeometric distribution.
iwishpdf
Compute the probability density function of the Wishart distribution
iwishrnd
Return a random matrix sampled from the inverse Wishart distribution with given parameters
jsucdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Johnson SU distribution with shape parameters ALPHA1 and ALPHA2.
jsupdf
For each element of X, compute the probability density function (PDF) at X of the Johnson SU distribution with shape parameters ALPHA1 and ALPHA2.
lognstat
Compute mean and variance of the lognormal distribution.
mnpdf
Compute the probability density function of the multinomial distribution.
mnrnd
Generate random samples from the multinomial distribution.
mvnpdf
Compute multivariate normal pdf for X given mean MU and covariance matrix SIGMA.
mvnrnd
Draw N random D-dimensional vectors from a multivariate Gaussian distribution with mean MU(NxD) and covariance matrix SIGMA(DxD).
mvncdf
Compute the cumulative distribution function of the multivariate normal distribution.
mvtcdf
Compute the cumulative distribution function of the multivariate Student's t distribution.
mvtpdf
Compute the probability density function of the multivariate Student's t distribution.
mvtrnd
Generate random samples from the multivariate t-distribution.
nakacdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Nakagami distribution with shape parameter M and scale parameter W.
nakainv
For each element of X, compute the quantile (the inverse of the CDF) at X of the Nakagami distribution with shape parameter M and scale parameter W.
nakapdf
For each element of X, compute the probability density function (PDF) at X of the Nakagami distribution with shape parameter M and scale parameter W.
nakarnd
Return a matrix of random samples from the Nakagami distribution with shape parameter M and scale W.
nbinstat
Compute mean and variance of the negative binomial distribution.
ncx2pdf
compute the non-central chi square probalitity density function at X , degree of freedom N , and non-centrality parameter LAMBDA .
normalise_distribution
Transform a set of data so as to be N(0,1) distributed according to an idea by van Albada and Robinson.
normstat
Compute mean and variance of the normal distribution.
pdf
Return probability density function of NAME function for value X.
poisstat
Compute mean and variance of the Poisson distribution.
qrandn
Returns random deviates drawn from a q-Gaussian distribution.
random
Generates pseudo-random numbers from a given one-, two-, or three-parameter distribution.
randsample
Elements sampled from a vector.
raylcdf
Compute the cumulative distribution function of the Rayleigh distribution.
raylinv
Compute the quantile of the Rayleigh distribution.
raylpdf
Compute the probability density function of the Rayleigh distribution.
raylrnd
Generate a matrix of random samples from the Rayleigh distribution.
raylstat
Compute mean and variance of the Rayleigh distribution.
tricdf
Compute the cumulative distribution function (CDF) at X of the triangular distribution with parameters A, B, and C on the interval [A, B].
triinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the triangular distribution with parameters A, B, and C on the interval [A, B].
tripdf
Compute the probability density function (PDF) at X of the triangular distribution with parameters A, B, and C on the interval [A, B].
trirnd
Return a matrix of random samples from the rectangular distribution with parameters A, B, and C on the interval [A, B].
tstat
Compute mean and variance of the t (Student) distribution.
unidstat
Compute mean and variance of the discrete uniform distribution.
unifstat
Compute mean and variance of the continuous uniform distribution.
vmpdf
Evaluates the Von Mises probability density function.
vmrnd
Draw random angles from a Von Mises distribution with mean MU and concentration K.
wblstat
Compute mean and variance of the Weibull distribution.
wishpdf
Compute the probability density function of the Wishart distribution
wishrnd
Return a random matrix sampled from the Wishart distribution with given parameters
betacdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Beta distribution with parameters A and B.
betainv
For each element of X, compute the quantile (the inverse of the CDF) at X of the Beta distribution with parameters A and B.
betapdf
For each element of X, compute the probability density function (PDF) at X of the Beta distribution with parameters A and B.
betarnd
Return a matrix of random samples from the Beta distribution with parameters A and B.
binocdf
For each element of X, compute the cumulative distribution function (CDF) at X of the binomial distribution with parameters N and P, where N is the number of trials and P is the probability of succ...
binoinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the binomial distribution with parameters N and P, where N is the number of trials and P is the probability of success.
binopdf
For each element of X, compute the probability density function (PDF) at X of the binomial distribution with parameters N and P, where N is the number of trials and P is the probability of success.
binornd
Return a matrix of random samples from the binomial distribution with parameters N and P, where N is the number of trials and P is the probability of success.
cauchy_cdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Cauchy distribution with location parameter LOCATION and scale parameter SCALE.
cauchy_inv
For each element of X, compute the quantile (the inverse of the CDF) at X of the Cauchy distribution with location parameter LOCATION and scale parameter SCALE.
cauchy_pdf
For each element of X, compute the probability density function (PDF) at X of the Cauchy distribution with location parameter LOCATION and scale parameter SCALE > 0.
cauchy_rnd
Return a matrix of random samples from the Cauchy distribution with parameters LOCATION and SCALE.
chi2cdf
For each element of X, compute the cumulative distribution function (CDF) at X of the chi-square distribution with N degrees of freedom.
chi2inv
For each element of X, compute the quantile (the inverse of the CDF) at X of the chi-square distribution with N degrees of freedom.
chi2pdf
For each element of X, compute the probability density function (PDF) at X of the chi-square distribution with N degrees of freedom.
chi2rnd
Return a matrix of random samples from the chi-square distribution with N degrees of freedom.
expcdf
For each element of X, compute the cumulative distribution function (CDF) at X of the exponential distribution with mean LAMBDA.
expinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the exponential distribution with mean LAMBDA.
exppdf
For each element of X, compute the probability density function (PDF) at X of the exponential distribution with mean LAMBDA.
exprnd
Return a matrix of random samples from the exponential distribution with mean LAMBDA.
fcdf
For each element of X, compute the cumulative distribution function (CDF) at X of the F distribution with M and N degrees of freedom.
finv
For each element of X, compute the quantile (the inverse of the CDF) at X of the F distribution with M and N degrees of freedom.
fpdf
For each element of X, compute the probability density function (PDF) at X of the F distribution with M and N degrees of freedom.
frnd
Return a matrix of random samples from the F distribution with M and N degrees of freedom.
gamcdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Gamma distribution with shape parameter A and scale B.
gaminv
For each element of X, compute the quantile (the inverse of the CDF) at X of the Gamma distribution with shape parameter A and scale B.
gampdf
For each element of X, return the probability density function (PDF) at X of the Gamma distribution with shape parameter A and scale B.
gamrnd
Return a matrix of random samples from the Gamma distribution with shape parameter A and scale B.
geocdf
For each element of X, compute the cumulative distribution function (CDF) at X of the geometric distribution with parameter P.
geoinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the geometric distribution with parameter P.
geopdf
For each element of X, compute the probability density function (PDF) at X of the geometric distribution with parameter P.
geornd
Return a matrix of random samples from the geometric distribution with parameter P.
hygecdf
Compute the cumulative distribution function (CDF) at X of the hypergeometric distribution with parameters T, M, and N.
hygeinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the hypergeometric distribution with parameters T, M, and N.
hygepdf
Compute the probability density function (PDF) at X of the hypergeometric distribution with parameters T, M, and N.
hygernd
Return a matrix of random samples from the hypergeometric distribution with parameters T, M, and N.
kolmogorov_smirnov_cdf
Return the cumulative distribution function (CDF) at X of the Kolmogorov-Smirnov distribution.
laplace_cdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Laplace distribution.
laplace_inv
For each element of X, compute the quantile (the inverse of the CDF) at X of the Laplace distribution.
laplace_pdf
For each element of X, compute the probability density function (PDF) at X of the Laplace distribution.
laplace_rnd
Return a matrix of random samples from the Laplace distribution.
logistic_cdf
For each element of X, compute the cumulative distribution function (CDF) at X of the logistic distribution.
logistic_inv
For each element of X, compute the quantile (the inverse of the CDF) at X of the logistic distribution.
logistic_pdf
For each element of X, compute the PDF at X of the logistic distribution.
logistic_rnd
Return a matrix of random samples from the logistic distribution.
logncdf
For each element of X, compute the cumulative distribution function (CDF) at X of the lognormal distribution with parameters MU and SIGMA.
logninv
For each element of X, compute the quantile (the inverse of the CDF) at X of the lognormal distribution with parameters MU and SIGMA.
lognpdf
For each element of X, compute the probability density function (PDF) at X of the lognormal distribution with parameters MU and SIGMA.
lognrnd
Return a matrix of random samples from the lognormal distribution with parameters MU and SIGMA.
nbincdf
For each element of X, compute the cumulative distribution function (CDF) at X of the negative binomial distribution with parameters N and P.
nbininv
For each element of X, compute the quantile (the inverse of the CDF) at X of the negative binomial distribution with parameters N and P.
nbinpdf
For each element of X, compute the probability density function (PDF) at X of the negative binomial distribution with parameters N and P.
nbinrnd
Return a matrix of random samples from the negative binomial distribution with parameters N and P.
normcdf
For each element of X, compute the cumulative distribution function (CDF) at X of the normal distribution with mean MU and standard deviation SIGMA.
norminv
For each element of X, compute the quantile (the inverse of the CDF) at X of the normal distribution with mean MU and standard deviation SIGMA.
normpdf
For each element of X, compute the probability density function (PDF) at X of the normal distribution with mean MU and standard deviation SIGMA.
normrnd
Return a matrix of random samples from the normal distribution with parameters mean MU and standard deviation SIGMA.
poisscdf
For each element of X, compute the cumulative distribution function (CDF) at X of the Poisson distribution with parameter LAMBDA.
poissinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the Poisson distribution with parameter LAMBDA.
poisspdf
For each element of X, compute the probability density function (PDF) at X of the Poisson distribution with parameter LAMBDA.
poissrnd
Return a matrix of random samples from the Poisson distribution with parameter LAMBDA.
stdnormal_cdf
For each element of X, compute the cumulative distribution function (CDF) at X of the standard normal distribution (mean = 0, standard deviation = 1).
stdnormal_inv
For each element of X, compute the quantile (the inverse of the CDF) at X of the standard normal distribution (mean = 0, standard deviation = 1).
stdnormal_pdf
For each element of X, compute the probability density function (PDF) at X of the standard normal distribution (mean = 0, standard deviation = 1).
stdnormal_rnd
Return a matrix of random samples from the standard normal distribution (mean = 0, standard deviation = 1).
tcdf
For each element of X, compute the cumulative distribution function (CDF) at X of the t (Student) distribution with N degrees of freedom.
tinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the t (Student) distribution with N degrees of freedom.
tpdf
For each element of X, compute the probability density function (PDF) at X of the T (Student) distribution with N degrees of freedom.
trnd
Return a matrix of random samples from the t (Student) distribution with N degrees of freedom.
unidcdf
For each element of X, compute the cumulative distribution function (CDF) at X of a discrete uniform distribution which assumes the integer values 1-N with equal probability.
unidinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the discrete uniform distribution which assumes the integer values 1-N with equal probability.
unidpdf
For each element of X, compute the probability density function (PDF) at X of a discrete uniform distribution which assumes the integer values 1-N with equal probability.
unidrnd
Return a matrix of random samples from the discrete uniform distribution which assumes the integer values 1-N with equal probability.
unifcdf
For each element of X, compute the cumulative distribution function (CDF) at X of the uniform distribution on the interval [A, B].
unifinv
For each element of X, compute the quantile (the inverse of the CDF) at X of the uniform distribution on the interval [A, B].
unifpdf
For each element of X, compute the probability density function (PDF) at X of the uniform distribution on the interval [A, B].
unifrnd
Return a matrix of random samples from the uniform distribution on [A, B].
wblcdf
Compute the cumulative distribution function (CDF) at X of the Weibull distribution with scale parameter SCALE and shape parameter SHAPE.
wblinv
Compute the quantile (the inverse of the CDF) at X of the Weibull distribution with scale parameter SCALE and shape parameter SHAPE.
wblpdf
Compute the probability density function (PDF) at X of the Weibull distribution with scale parameter SCALE and shape parameter SHAPE.
wblrnd
Return a matrix of random samples from the Weibull distribution with parameters SCALE and SHAPE.
wienrnd
Return a simulated realization of the D-dimensional Wiener Process on the interval [0, T].

Descriptive statistics

combnk
Return all combinations of K elements in DATA.
dcov
Distance correlation, covariance and correlation statistics.
geomean
Compute the geometric mean.
harmmean
Compute the harmonic mean.
jackknife
Compute jackknife estimates of a parameter taking one or more given samples as parameters.
nanmax
Find the maximal element while ignoring NaN values.
nanmean
Compute the mean value while ignoring NaN values.
nanmedian
Compute the median of data while ignoring NaN values.
nanmin
Find the minimal element while ignoring NaN values.
nanstd
Compute the standard deviation while ignoring NaN values.
nansum
Compute the sum while ignoring NaN values.
nanvar
Compute the variance while ignoring NaN values.
trimmean
Compute the trimmed mean.
tabulate
Compute a frequency table.
cloglog
Return the complementary log-log function of X.
crosstab
Create a cross-tabulation (contingency table) T from data vectors.
logit
Compute the logit for each value of P
probit
Return the probit (the quantile of the standard normal distribution) for each element of P.

Experimental design

fullfact
Full factorial design.
ff2n
Full-factor design with n binary terms.

Regression

anova1
Perform a one-way analysis of variance (ANOVA) for comparing the means of two or more groups of data under the null hypothesis that the groups are drawn from the same distribution, i.e. the group ...
anovan
Perform a multi-way analysis of variance (ANOVA).
canoncorr
Canonical correlation analysis
crossval
Perform cross validation on given data.
monotone_smooth
Produce a smooth monotone increasing approximation to a sampled functional dependence
pca
Performs a principal component analysis on a data matrix X
pcacov
Perform principal component analysis on the nxn covariance matrix X
pcares
Calulate residuals from principal component analysis
plsregress
Calculate partial least squares regression
princomp
Performs a principal component analysis on a NxP data matrix X
regress
Multiple Linear Regression using Least Squares Fit of Y on X with the model 'y = X * beta + e'.
regress_gp
Linear scalar regression using gaussian processes.
stepwisefit
This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the Li...

Plots

boxplot
Produce a box plot.
confusionchart
Display a chart of a confusion matrix.
dendrogram
Plot a dendrogram of a hierarchical binary cluster tree.
gscatter
Draw a scatter plot with grouped data.
histfit
Plot histogram with superimposed fitted normal density.
hist3
Produce bivariate (2D) histogram counts or plots.
normplot
Produce normal probability plot for each column of X.
repanova
Perform a repeated measures analysis of variance (Repeated ANOVA).
silhouette
Compute the silhouette values of clustered data and show them on a plot.
violin
Produce a Violin plot of the data X.
wblplot
Plot a column vector DATA on a Weibull probability plot using rank regression.
ppplot
Perform a PP-plot (probability plot).
qqplot
Perform a QQ-plot (quantile plot).

Models

hmmestimate
Estimate the matrix of transition probabilities and the matrix of output probabilities of a given sequence of outputs and states generated by a hidden Markov model.
hmmgenerate
Generate an output sequence and hidden states of a hidden Markov model.
hmmviterbi
Use the Viterbi algorithm to find the Viterbi path of a hidden Markov model given a sequence of outputs.
mhsample
Draws NSAMPLES samples from a target stationary distribution PDF using Metropolis-Hastings algorithm.
slicesample
Draws NSAMPLES samples from a target stationary distribution PDF using slice sampling of Radford M.
logistic_regression
Perform ordinal logistic regression.

Hypothesis testing

anderson_darling_test
Test the hypothesis that X is selected from the given distribution using the Anderson-Darling test.
kruskalwallis
Perform a Kruskal-Wallis test, the non-parametric alternative of a one-way analysis of variance (ANOVA), for comparing the means of two or more groups of data under the null hypothesis that the gro...
runstest
Runs test for detecting serial correlation in the vector X.
signtest
Test for median.
ttest
Test for mean of a normal sample with unknown variance.
ttest2
Test for mean of a normal sample with known variance.
vartest
Perform a F-test for equal variances.
vartest2
Perform a F-test for equal variances.
ztest
Test for mean of a normal sample with known variance.
anova
Perform a one-way analysis of variance (ANOVA).
bartlett_test
Perform a Bartlett test for the homogeneity of variances in the data vectors X1, X2, ..., XK, where K > 1.
chisquare_test_homogeneity
Given two samples X and Y, perform a chisquare test for homogeneity of the null hypothesis that X and Y come from the same distribution, based on the partition induced by the (strictly increasing) ...
chisquare_test_independence
Perform a chi-square test for independence based on the contingency table X.
cor_test
Test whether two samples X and Y come from uncorrelated populations.
f_test_regression
Perform an F test for the null hypothesis rr * b = r in a classical normal regression model y = X * b + e.
hotelling_test
For a sample X from a multivariate normal distribution with unknown mean and covariance matrix, test the null hypothesis that 'mean (X) == M'.
hotelling_test_2
For two samples X from multivariate normal distributions with the same number of variables (columns), unknown means and unknown equal covariance matrices, test the null hypothesis 'mean (X) == mean...
kolmogorov_smirnov_test
Perform a Kolmogorov-Smirnov test of the null hypothesis that the sample X comes from the (continuous) distribution DIST.
kolmogorov_smirnov_test_2
Perform a 2-sample Kolmogorov-Smirnov test of the null hypothesis that the samples X and Y come from the same (continuous) distribution.
kruskal_wallis_test
Perform a Kruskal-Wallis one-factor analysis of variance.
manova
Perform a one-way multivariate analysis of variance (MANOVA).
mcnemar_test
For a square contingency table X of data cross-classified on the row and column variables, McNemar's test can be used for testing the null hypothesis of symmetry of the classification probabilities.
prop_test_2
If X1 and N1 are the counts of successes and trials in one sample, and X2 and N2 those in a second one, test the null hypothesis that the success probabilities P1 and P2 are the same.
run_test
Perform a chi-square test with 6 degrees of freedom based on the upward runs in the columns of X.
sign_test
For two matched-pair samples X and Y, perform a sign test of the null hypothesis PROB (X > Y) == PROB (X < Y) == 1/2.
t_test
For a sample X from a normal distribution with unknown mean and variance, perform a t-test of the null hypothesis 'mean (X) == M'.
t_test_2
For two samples x and y from normal distributions with unknown means and unknown equal variances, perform a two-sample t-test of the null hypothesis of equal means.
t_test_regression
Perform a t test for the null hypothesis 'RR * B = R' in a classical normal regression model 'Y = X * B + E'.
u_test
For two samples X and Y, perform a Mann-Whitney U-test of the null hypothesis PROB (X > Y) == 1/2 == PROB (X < Y).
var_test
For two samples X and Y from normal distributions with unknown means and unknown variances, perform an F-test of the null hypothesis of equal variances.
welch_test
For two samples X and Y from normal distributions with unknown means and unknown and not necessarily equal variances, perform a Welch test of the null hypothesis of equal means.
wilcoxon_test
For two matched-pair sample vectors X and Y, perform a Wilcoxon signed-rank test of the null hypothesis PROB (X > Y) == 1/2.
z_test
Perform a Z-test of the null hypothesis 'mean (X) == M' for a sample X from a normal distribution with unknown mean and known variance V.
z_test_2
For two samples X and Y from normal distributions with unknown means and known variances V_X and V_Y, perform a Z-test of the hypothesis of equal means.

Fitting

fitgmdist
Fit a Gaussian mixture model with K components to DATA.
gamfit
Calculate gamma distribution parameters.

Clustering

cluster
Define clusters from an agglomerative hierarchical cluster tree.
clusterdata
Wrapper function for 'linkage' and 'cluster'.
cmdscale
Classical multidimensional scaling of a matrix.
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 the NxD table DATA.
linkage
Produce a hierarchical clustering dendrogram
mahal
Mahalanobis' D-square distance.
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.
squareform
Interchange between distance matrix and distance vector formats.

Reading and Writing

caseread
Read case names from an ascii file.
casewrite
Write case names to an ascii file.
tblread
Read tabular data from an ascii file.
tblwrite
Write tabular data to an ascii file.

Cvpartition (class of set partitions for cross-validation, used in crossval)

@cvpartition/cvpartition
Create a partition object for cross validation.
@cvpartition/display
Display a cvpartition object.
@cvpartition/get
Get a field from a 'cvpartition' object.
@cvpartition/repartition
Return a new cvpartition object.
@cvpartition/set
Set field(s) in a 'cvpartition' object.
@cvpartition/test
Return logical vector for testing-subset indices from a cvpartition object.
@cvpartition/training
Return logical vector for training-subset indices from a cvpartition object.

Categorical data

grp2idx
Get index for group variables.

Classification Performance Evaluation

confusionchart
Display a chart of a confusion matrix.
confusionmat
Compute a confusion matrix for classification problems

Other

sigma_pts
Calculates 2*N+1 sigma points in N dimensions.
ismissing
Find missing data in a matrix or a string array.
rmmissing
Remove missing or incomplete data from an array or a matrix.

Package: statistics