Select Category: Clustering Classification Classes Clustering Classes CVpartition Regression Classes Data Manipulation Descriptive Statistics Distribution Classes Distribution Fitting Distribution Functions Distribution Statistics Distribution Wrappers Experimental Design Machine Learning Model Fitting Hypothesis Testing I/O Plotting Regression Transforms

Clustering

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.
crossval	Perform cross validation on given data.
editDistance	Compute the edit (Levenshtein) distance between strings or documents.
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 matrix DATA.
knnsearch	Find k-nearest neighbors from input data.
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.
procrustes	Procrustes Analysis.
rangesearch	Find all neighbors within specified distance from input data.
slicesample	Draws NSAMPLES samples from a target stationary distribution PDF using slice sampling of Radford M.
squareform	Interchange between distance matrix and distance vector formats.

Classification Classes

ClassificationDiscriminant	Create a ClassificationDiscriminant class object containing a discriminant analysis model.
ClassificationGAM	Create a ClassificationGAM class object containing a generalized additive classification model.
ClassificationKNN	Create a ClassificationKNN class object containing a k-Nearest Neighbor classification model.
ClassificationNeuralNetwork	Create a ClassificationNeuralNetwork class object containing a Neural Network classification model.
ClassificationPartitionedModel	Create a ClassificationPartitionedModel class for cross-validation of classification models.
ClassificationSVM	Create a ClassificationSVM class object containing a Support Vector Machine classification model for one-class or two-class problems.
CompactClassificationDiscriminant	A CompactClassificationDiscriminant object is a compact version of a discriminant analysis model, ClassificationDiscriminant.
CompactClassificationGAM	A CompactClassificationGAM object is a compact version of a Generalized Additive Model, ClassificationGAM.
CompactClassificationNeuralNetwork	A CompactClassificationNeuralNetwork object is a compact version of a discriminant analysis model, CompactClassificationNeuralNetwork.
CompactClassificationSVM	A CompactClassificationSVM object is a compact version of a support vectors machine model, CompactClassificationSVM.
ConfusionMatrixChart	Create object CMC, a Confusion Matrix Chart object.

Clustering Classes

CalinskiHarabaszEvaluation	A Calinski-Harabasz object to evaluate clustering solutions.
ClusterCriterion	A clustering evaluation object as created by 'evalclusters'.
DaviesBouldinEvaluation	A Davies-Bouldin object to evaluate clustering solutions.
GapEvaluation	A gap object to evaluate clustering solutions.
SilhouetteEvaluation	A silhouette object to evaluate clustering solutions.

CVpartition

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

Regression Classes

RegressionGAM

Create a RegressionGAM class object containing a Generalised Additive Model (GAM) for regression.

Data Manipulation

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. 'missing' values are determined by the data type of A as identified by the function ismissing, curently defined as:
grp2idx	Get index for group variables.
ismissing	Find missing data in a numeric or string array.
isoutlier	Find outliers in data
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	Calculate a frequency table.

Descriptive Statistics

cdfcalc	Calculate an empirical cumulative distribution function.
cl_multinom	Confidence level of multinomial portions.
geomean	Compute the geometric mean of X.
grpstats	Summary statistics by group. 'grpstats' computes groupwise summary statistics, for data in a matrix X. 'grpstats' treats NaNs as missing values, and removes them.
harmmean	Compute the harmonic mean of X.
jackknife	Compute jackknife estimates of a parameter taking one or more given samples as parameters.
mad	Compute the mean or median absolute deviation (MAD) of the elements of X.
mean	Compute the mean of the elements of X.
median	Compute the median value of the elements of X.
nanmax	Find the maximum while ignoring NaN values.
nanmin	Find the minimum while ignoring NaN values.
nansum	Compute the sum while ignoring NaN values.
std	Compute the standard deviation of the elements of the vector X.
trimmean	Compute the trimmed mean.
var	Compute the variance of the elements of the vector X.

Distribution Classes

BetaDistribution	Beta probability distribution object.
BinomialDistribution	Binomial probability distribution object.
BirnbaumSaundersDistribution	Gamma probability distribution object.
BurrDistribution	Burr probability distribution object.
ExponentialDistribution	Exponential probability distribution object.
ExtremeValueDistribution	Extreme value probability distribution object.
GammaDistribution	Gamma probability distribution object.
GeneralizedExtremeValueDistribution	Generalized extreme value probability distribution object.
GeneralizedParetoDistribution	Generalized Pareto probability distribution object.
HalfNormalDistribution	Half-normal probability distribution object.
InverseGaussianDistribution	Logistic probability distribution object.
LogisticDistribution	Logistic probability distribution object.
LoglogisticDistribution	Loglogistic probability distribution object.
LognormalDistribution	Lognormal probability distribution object.
LoguniformDistribution	Log-uniform probability distribution object.
MultinomialDistribution	Multinomial probability distribution object.
NakagamiDistribution	Normal probability distribution object.
NegativeBinomialDistribution	Negative binomial probability distribution object.
NormalDistribution	Normal probability distribution object.
PiecewiseLinearDistribution	Piecewise linear probability distribution object.
PoissonDistribution	Poisson probability distribution object.
RayleighDistribution	Rayleigh probability distribution object.
RicianDistribution	Rician probability distribution object.
tLocationScaleDistribution	Weibull probability distribution object.
TriangularDistribution	Triangular probability distribution object.
UniformDistribution	Continuous uniform probability distribution object.
WeibullDistribution	Weibull probability distribution object.

Distribution Fitting

betafit	Estimate parameters and confidence intervals for the Beta distribution.
betalike	Negative log-likelihood for the Beta distribution.
binofit	Estimate parameter and confidence intervals for the binomial distribution.
binolike	Negative log-likelihood for the binomial distribution.
bisafit	Estimate mean and confidence intervals for the Birnbaum-Saunders distribution.
bisalike	Negative log-likelihood for the Birnbaum-Saunders distribution.
burrfit	Estimate mean and confidence intervals for the Burr type XII distribution.
burrlike	Negative log-likelihood for the Burr type XII distribution.
evfit	Estimate parameters and confidence intervals for the extreme value distribution.
evlike	Negative log-likelihood for the extreme value distribution.
expfit	Estimate mean and confidence intervals for the exponential distribution.
explike	Negative log-likelihood for the exponential distribution.
gamfit	Estimate parameters and confidence intervals for the Gamma distribution.
gamlike	Negative log-likelihood for the Gamma distribution.
geofit	Estimate parameter and confidence intervals for the geometric distribution.
gevfit_lmom	Find an estimator (PARAMHAT) of the generalized extreme value (GEV) distribution fitting DATA using the method of L-moments.
gevfit	Estimate parameters and confidence intervals for the generalized extreme value (GEV) distribution.
gevlike	Negative log-likelihood for the generalized extreme value (GEV) distribution.
gpfit	Estimate parameters and confidence intervals for the generalized Pareto distribution.
gplike	Negative log-likelihood for the generalized Pareto distribution.
gumbelfit	Estimate parameters and confidence intervals for Gumbel distribution.
gumbellike	Negative log-likelihood for the extreme value distribution.
hnfit	Estimate parameters and confidence intervals for the half-normal distribution.
hnlike	Negative log-likelihood for the half-normal distribution.
invgfit	Estimate mean and confidence intervals for the inverse Gaussian distribution.
invglike	Negative log-likelihood for the inverse Gaussian distribution.
logifit	Estimate mean and confidence intervals for the logistic distribution.
logilike	Negative log-likelihood for the logistic distribution.
loglfit	Estimate mean and confidence intervals for the log-logistic distribution.
logllike	Negative log-likelihood for the log-logistic distribution.
lognfit	Estimate parameters and confidence intervals for the lognormal distribution.
lognlike	Negative log-likelihood for the lognormal distribution.
nakafit	Estimate mean and confidence intervals for the Nakagami distribution.
nakalike	Negative log-likelihood for the Nakagami distribution.
nbinfit	Estimate parameter and confidence intervals for the negative binomial distribution.
nbinlike	Negative log-likelihood for the negative binomial distribution.
normfit	Estimate parameters and confidence intervals for the normal distribution.
normlike	Negative log-likelihood for the normal distribution.
poissfit	Estimate parameter and confidence intervals for the Poisson distribution.
poisslike	Negative log-likelihood for the Poisson distribution.
raylfit	Estimate parameter and confidence intervals for the Rayleigh distribution.
rayllike	Negative log-likelihood for the Rayleigh distribution.
ricefit	Estimate parameters and confidence intervals for the Gamma distribution.
ricelike	Negative log-likelihood for the Rician distribution.
tlsfit	Estimate parameters and confidence intervals for the Location-scale Student's T distribution.
tlslike	Negative log-likelihood for the location-scale Student's T distribution.
unidfit	Estimate parameter and confidence intervals for the discrete uniform distribution.
unifit	Estimate parameter and confidence intervals for the continuous uniform distribution.
wblfit	Estimate parameters and confidence intervals for the Weibull distribution.
wbllike	Negative log-likelihood for the Weibull distribution.

Distribution Functions

betacdf	Beta cumulative distribution function (CDF).
betainv	Inverse of the Beta distribution (iCDF).
betapdf	Beta probability density function (PDF).
betarnd	Random arrays from the Beta distribution.
binocdf	Binomial cumulative distribution function (CDF).
binoinv	Inverse of the Binomial cumulative distribution function (iCDF).
binopdf	Binomial probability density function (PDF).
binornd	Random arrays from the Binomial distribution.
bisacdf	Birnbaum-Saunders cumulative distribution function (CDF).
bisainv	Inverse of the Birnbaum-Saunders cumulative distribution function (iCDF).
bisapdf	Birnbaum-Saunders probability density function (PDF).
bisarnd	Random arrays from the Birnbaum-Saunders distribution.
burrcdf	Burr type XII cumulative distribution function (CDF).
burrinv	Inverse of the Burr type XII cumulative distribution function (iCDF).
burrpdf	Burr type XII probability density function (PDF).
burrrnd	Random arrays from the Burr type XII distribution.
bvncdf	Bivariate normal cumulative distribution function (CDF).
bvtcdf	Bivariate Student's t cumulative distribution function (CDF).
cauchycdf	Cauchy cumulative distribution function (CDF).
cauchyinv	Inverse of the Cauchy cumulative distribution function (iCDF).
cauchypdf	Cauchy probability density function (PDF).
cauchyrnd	Random arrays from the Cauchy distribution.
chi2cdf	Chi-squared cumulative distribution function (CDF).
chi2inv	Inverse of the chi-squared cumulative distribution function (iCDF).
chi2pdf	Chi-squared probability density function (PDF).
chi2rnd	Random arrays from the chi-squared distribution.
copulacdf	Copula family cumulative distribution functions (CDF).
copulapdf	Copula family probability density functions (PDF).
copularnd	Random arrays from the copula family distributions.
evcdf	Extreme value cumulative distribution function (CDF).
evinv	Inverse of the extreme value cumulative distribution function (iCDF).
evpdf	Extreme value probability density function (PDF).
evrnd	Random arrays from the extreme value distribution.
expcdf	Exponential cumulative distribution function (CDF).
expinv	Inverse of the exponential cumulative distribution function (iCDF).
exppdf	Exponential probability density function (PDF).
exprnd	Random arrays from the exponential distribution.
fcdf	F-cumulative distribution function (CDF).
finv	Inverse of the F-cumulative distribution function (iCDF).
fpdf	F-probability density function (PDF).
frnd	Random arrays from the F-distribution.
gamcdf	Gamma cumulative distribution function (CDF).
gaminv	Inverse of the Gamma cumulative distribution function (iCDF).
gampdf	Gamma probability density function (PDF).
gamrnd	Random arrays from the Gamma distribution.
geocdf	Geometric cumulative distribution function (CDF).
geoinv	Inverse of the geometric cumulative distribution function (iCDF).
geopdf	Geometric probability density function (PDF).
geornd	Random arrays from the geometric distribution.
gevcdf	Generalized extreme value (GEV) cumulative distribution function (CDF).
gevinv	Inverse of the generalized extreme value (GEV) cumulative distribution function (iCDF).
gevpdf	Generalized extreme value (GEV) probability density function (PDF).
gevrnd	Random arrays from the generalized extreme value (GEV) distribution.
gpcdf	Generalized Pareto cumulative distribution function (CDF).
gpinv	Inverse of the generalized Pareto cumulative distribution function (iCDF).
gppdf	Generalized Pareto probability density function (PDF).
gprnd	Random arrays from the generalized Pareto distribution.
gumbelcdf	Gumbel cumulative distribution function (CDF).
gumbelinv	Inverse of the Gumbel cumulative distribution function (iCDF).
gumbelpdf	Gumbel probability density function (PDF).
gumbelrnd	Random arrays from the Gumbel distribution.
hncdf	Half-normal cumulative distribution function (CDF).
hninv	Inverse of the half-normal cumulative distribution function (iCDF).
hnpdf	Half-normal probability density function (PDF).
hnrnd	Random arrays from the half-normal distribution.
hygecdf	Hypergeometric cumulative distribution function (CDF).
hygeinv	Inverse of the hypergeometric cumulative distribution function (iCDF).
hygepdf	Hypergeometric probability density function (PDF).
hygernd	Random arrays from the hypergeometric distribution.
invgcdf	Inverse Gaussian cumulative distribution function (CDF).
invginv	Inverse of the inverse Gaussian cumulative distribution function (iCDF).
invgpdf	Inverse Gaussian probability density function (PDF).
invgrnd	Random arrays from the inverse Gaussian distribution.
iwishpdf	Compute the probability density function of the inverse Wishart distribution.
iwishrnd	Return a random matrix sampled from the inverse Wishart distribution with given parameters.
jsucdf	Johnson SU cumulative distribution function (CDF).
jsupdf	Johnson SU probability density function (PDF).
laplacecdf	Laplace cumulative distribution function (CDF).
laplaceinv	Inverse of the Laplace cumulative distribution function (iCDF).
laplacepdf	Laplace probability density function (PDF).
laplacernd	Random arrays from the Laplace distribution.
logicdf	Logistic cumulative distribution function (CDF).
logiinv	Inverse of the logistic cumulative distribution function (iCDF).
logipdf	Logistic probability density function (PDF).
logirnd	Random arrays from the logistic distribution.
loglcdf	Loglogistic cumulative distribution function (CDF).
loglinv	Inverse of the log-logistic cumulative distribution function (iCDF).
loglpdf	Loglogistic probability density function (PDF).
loglrnd	Random arrays from the loglogistic distribution.
logncdf	Lognormal cumulative distribution function (CDF).
logninv	Inverse of the lognormal cumulative distribution function (iCDF).
lognpdf	Lognormal probability density function (PDF).
lognrnd	Random arrays from the lognormal distribution.
mnpdf	Multinomial probability density function (PDF).
mnrnd	Random arrays from the multinomial distribution.
mvncdf	Multivariate normal cumulative distribution function (CDF).
mvnpdf	Multivariate normal probability density function (PDF).
mvnrnd	Random vectors from the multivariate normal distribution.
mvtcdf	Multivariate Student's t cumulative distribution function (CDF).
mvtpdf	Multivariate Student's t probability density function (PDF).
mvtrnd	Random vectors from the multivariate Student's t distribution.
mvtcdfqmc	Quasi-Monte-Carlo computation of the multivariate Student's T CDF.
nakacdf	Nakagami cumulative distribution function (CDF).
nakainv	Inverse of the Nakagami cumulative distribution function (iCDF).
nakapdf	Nakagami probability density function (PDF).
nakarnd	Random arrays from the Nakagami distribution.
nbincdf	Negative binomial cumulative distribution function (CDF).
nbininv	Inverse of the negative binomial cumulative distribution function (iCDF).
nbinpdf	Negative binomial probability density function (PDF).
nbinrnd	Random arrays from the negative binomial distribution.
ncfcdf	Noncentral F-cumulative distribution function (CDF).
ncfinv	Inverse of the noncentral F-cumulative distribution function (iCDF).
ncfpdf	Noncentral F-probability density function (PDF).
ncfrnd	Random arrays from the noncentral F-distribution.
nctcdf	Noncentral t-cumulative distribution function (CDF).
nctinv	Inverse of the non-central t-cumulative distribution function (iCDF).
nctpdf	Noncentral t-probability density function (PDF).
nctrnd	Random arrays from the noncentral t-distribution.
ncx2cdf	Noncentral chi-squared cumulative distribution function (CDF).
ncx2inv	Inverse of the noncentral chi-squared cumulative distribution function (iCDF).
ncx2pdf	Noncentral chi-squared probability distribution function (PDF).
ncx2rnd	Random arrays from the noncentral chi-squared distribution.
normcdf	Normal cumulative distribution function (CDF).
norminv	Inverse of the normal cumulative distribution function (iCDF).
normpdf	Normal probability density function (PDF).
normrnd	Random arrays from the normal distribution.
plcdf	Piecewise linear cumulative distribution function (CDF).
plinv	Inverse of the piecewise linear distribution (iCDF).
plpdf	Piecewise linear probability density function (PDF).
plrnd	Random arrays from the piecewise linear distribution.
poisscdf	Poisson cumulative distribution function (CDF).
poissinv	Inverse of the Poisson cumulative distribution function (iCDF).
poisspdf	Poisson probability density function (PDF).
poissrnd	Random arrays from the Poisson distribution.
raylcdf	Rayleigh cumulative distribution function (CDF).
raylinv	Inverse of the Rayleigh cumulative distribution function (iCDF).
raylpdf	Rayleigh probability density function (PDF).
raylrnd	Random arrays from the Rayleigh distribution.
ricecdf	Rician cumulative distribution function (CDF).
riceinv	Inverse of the Rician distribution (iCDF).
ricepdf	Rician probability density function (PDF).
ricernd	Random arrays from the Rician distribution.
tcdf	Student's T cumulative distribution function (CDF).
tinv	Inverse of the Student's T cumulative distribution function (iCDF).
tpdf	Student's T probability density function (PDF).
trnd	Random arrays from the Student's T distribution.
tlscdf	Location-scale Student's T cumulative distribution function (CDF).
tlsinv	Inverse of the location-scale Student's T cumulative distribution function (iCDF).
tlspdf	Location-scale Student's T probability density function (PDF).
tlsrnd	Random arrays from the location-scale Student's T distribution.
tricdf	Triangular cumulative distribution function (CDF).
triinv	Inverse of the triangular cumulative distribution function (iCDF).
tripdf	Triangular probability density function (PDF).
trirnd	Random arrays from the triangular distribution.
unidcdf	Discrete uniform cumulative distribution function (CDF).
unidinv	Inverse of the discrete uniform cumulative distribution function (iCDF).
unidpdf	Discrete uniform probability density function (PDF).
unidrnd	Random arrays from the discrete uniform distribution.
unifcdf	Continuous uniform cumulative distribution function (CDF).
unifinv	Inverse of the continuous uniform cumulative distribution function (iCDF).
unifpdf	Continuous uniform probability density function (PDF).
unifrnd	Random arrays from the continuous uniform distribution.
vmcdf	Von Mises probability density function (PDF).
vminv	Inverse of the von Mises cumulative distribution function (iCDF).
vmpdf	Von Mises probability density function (PDF).
vmrnd	Random arrays from the von Mises distribution.
wblcdf	Weibull cumulative distribution function (CDF).
wblinv	Inverse of the Weibull cumulative distribution function (iCDF).
wblpdf	Weibull probability density function (PDF).
wblrnd	Random arrays from the Weibull distribution.
wienrnd	Return a simulated realization of the D-dimensional Wiener Process on the interval [0, T].
wishpdf	Compute the probability density function of the Wishart distribution
wishrnd	Return a random matrix sampled from the Wishart distribution with given parameters

Distribution Statistics

betastat	Compute statistics of the Beta distribution.
binostat	Compute statistics of the binomial distribution.
bisastat	Compute statistics of the Birnbaum-Saunders distribution.
burrstat	Compute statistics of the Burr type XII distribution.
chi2stat	Compute statistics of the chi-squared distribution.
evstat	Compute statistics of the extreme value distribution.
expstat	Compute statistics of the exponential distribution.
fstat	Compute statistics of the F-distribution.
gamstat	Compute statistics of the Gamma distribution.
geostat	Compute statistics of the geometric distribution.
gevstat	Compute statistics of the generalized extreme value distribution.
gpstat	Compute statistics of the generalized Pareto distribution.
hnstat	Compute statistics of the half-normal distribution.
hygestat	Compute statistics of the hypergeometric distribution.
invgstat	Compute statistics of the inverse Gaussian distribution.
logistat	Compute statistics of the logistic distribution.
loglstat	Compute statistics of the loglogistic distribution.
lognstat	Compute statistics of the lognormal distribution.
nakastat	Compute statistics of the Nakagami distribution.
nbinstat	Compute statistics of the negative binomial distribution.
ncfstat	Compute statistics for the noncentral F-distribution.
nctstat	Compute statistics for the noncentral t-distribution.
ncx2stat	Compute statistics for the noncentral chi-squared distribution.
normstat	Compute statistics of the normal distribution.
plstat	Compute statistics of the piecewise linear distribution.
poisstat	Compute statistics of the Poisson distribution.
raylstat	Compute statistics of the Rayleigh distribution.
ricestat	Compute statistics of the Rician distribution.
tlsstat	Compute statistics of the location-scale Student's T distribution.
tristat	Compute statistics of the Triangular distribution.
tstat	Compute statistics of the Student's T distribution.
unidstat	Compute statistics of the discrete uniform cumulative distribution.
unifstat	Compute statistics of the continuous uniform cumulative distribution.
wblstat	Compute statistics of the Weibull distribution.

Distribution Wrappers

cdf	Return the CDF of a univariate distribution evaluated at X.
fitdist	Create probability distribution object.
icdf	Return the inverse CDF of a univariate distribution evaluated at P.
makedist	Create probability distribution object.
mle	Compute maximum likelihood estimates.
pdf	Return the PDF of a univariate distribution evaluated at X.
random	Random arrays from a given one-, two-, or three-parameter distribution.

Experimental Design

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

fcnnpredict	Make predictions from a fully connected Neural Network.
fcnntrain	Train a fully connected Neural Network.
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	This function predicts new labels from a testing instance matrtix based on an SVM MODEL created with 'svmtrain'.
svmtrain	This function trains an SVM MODEL based on known LABELS and their corresponding DATA which comprise an instance matrtix.

Model Fitting

fitcdiscr	Fit a Linear Discriminant Analysis classification model.
fitcgam	Fit a Generalized Additive Model (GAM) for binary classification.
fitcknn	Fit a k-Nearest Neighbor classification model.
fitcnet	Fit a Neural Network classification model.
fitcsvm	Fit a Support Vector Machine classification model.
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.
fitrgam	Fit a Generalised Additive Model (GAM) for regression.

Hypothesis Testing

adtest	Anderson-Darling goodness-of-fit hypothesis test.
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 distributions with the same mean.
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).
correlation_test	Perform a correlation coefficient test whether two samples X and Y come from uncorrelated populations.
fishertest	Fisher's exact test.
friedman	Performs the nonparametric Friedman's test to compare column effects in a two-way layout. friedman tests the null hypothesis that the column effects are all the same against the alternative that they are not all the same.
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), for comparing the means of two or more groups of data under the null hypothesis that the groups are drawn from the same population, ...
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).
mcnemar_test	Perform a McNemar's test on paired nominal data.
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.
regression_ftest	F-test for General Linear Regression Analysis
regression_ttest	Perform a linear regression t-test.
runstest	Run test for randomness in the vector X.
sampsizepwr	Sample size and power calculation for hypothesis test.
signrank	Wilcoxon signed rank test for median.
signtest	Signed test for median.
tiedrank	Compute rank adjusted for ties.
ttest	Test for mean of a normal sample with unknown variance.
ttest2	Perform a t-test to compare the means of two groups of data under the null hypothesis that the groups are drawn from distributions with the same mean.
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.

I/O

libsvmread	This function reads the labels and the corresponding instance_matrix from a LIBSVM data file and stores them in LABELS and DATA respectively.
libsvmwrite	This function saves the labels and the corresponding instance_matrix in a file specified by FILENAME.
loadmodel	Load a Classification or Regression model from a file.

Plotting

bar3	Plot a 3D bar graph.
bar3h	Plot a horizontal 3D bar graph.
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.
einstein	Plots the tiling of the basic clusters of einstein tiles.
gscatter	Draw a scatter plot with grouped data.
histfit	Plot histogram with superimposed distribution fit.
hist3	Produce bivariate (2D) histogram counts or plots.
manovacluster	Cluster group means using manova1 output.
normplot	Produce normal probability plot of the data in X.
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 X.
wblplot	Plot a column vector DATA on a Weibull probability plot using rank regression.

Regression

canoncorr	Canonical correlation analysis.
cholcov	Cholesky-like decomposition for covariance matrix.
dcov	Distance correlation, covariance and correlation statistics.
glmfit	Perform generalized linear model fitting.
logistic_regression	Perform ordinal logistic regression.
mnrfit	Perform logistic regression for binomial responses or multiple ordinal responses.
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 covariance matrix
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 X.
regress	Multiple Linear Regression using Least Squares Fit of Y on X with the model 'y = X * beta + e'.
regress_gp	Regression using Gaussian Processes.
ridge	Ridge regression.
stepwisefit	Linear regression with stepwise variable selection.

Transforms

logit	Compute the logit for each value of P
probit	Probit transformation