Select Category: Descriptive Statistics Data Manipulation Hypothesis Testing Experimental Design Regression Supervised Learning Clustering Nearest Neighbors Anomaly Detection Dimensionality Reduction Model Evaluation Markov Models Random Sampling Distribution Classes Distribution Fitting Distribution Functions Distribution Statistics Distribution Wrappers Plotting I/O Utilities

Descriptive Statistics

cdfcalc	Calculate an empirical cumulative distribution function.
cl_multinom	Confidence level of multinomial portions.
dcov	Distance correlation, covariance and correlation statistics.
ecdf	Empirical (Kaplan-Meier) cumulative distribution function.
geomean	Compute the geometric mean of X.
grpstats	Summary statistics by group.
harmmean	Compute the harmonic mean of X.
jackknife	Compute jackknife estimates of a parameter taking one or more given samples as parameters.
ksdensity	Kernel smoothing density estimate.
mvksdensity	Multivariate kernel smoothing density estimate.
nancov	Compute the covariance matrix while ignoring NaN values.
nanmax	Find the maximum while ignoring NaN values.
nanmean	Compute the mean while ignoring NaN values.
nanmedian	Compute the median while ignoring NaN values.
nanmin	Find the minimum 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.
partialcorr	Linear or rank partial correlation coefficients.
partialcorri	Partial correlation of each response with each predictor, adjusting for the remaining predictors.
tabulate	Create a frequency table of unique values in vector X.
trimmean	Compute the trimmed mean.

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.
dummyvar	Create dummy variables.
fillmissing	Fill missing data in arrays.
grp2idx	Get index for grouping variable.
ismissing	Find missing data in arrays.
isoutlier	Find outliers in data
multiway	Solve the multiway number partitioning problem.
normalise_distribution	Transform a set of data so as to be N(0,1) distributed according to an idea by van Albada and Robinson.
randsample	Sample elements from a vector.
rmmissing	Remove missing data from arrays.
standardizeMissing	Replace selected values by standard missing values.
tiedrank	X may be a vector or an array.

Hypothesis Testing

adtest	Anderson-Darling goodness-of-fit hypothesis test.
anova	Object-oriented interface for analysis of variance.
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).
ansaribradley	Ansari-Bradley two-sample test for equal dispersions.
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 to determine whether two samples X and Y come from uncorrelated populations.
dwtest	Durbin-Watson test for autocorrelation in linear regression residuals.
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.
jbtest	Jarque-Bera hypothesis test of composite normality.
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.
lillietest	Lilliefors goodness-of-fit hypothesis test.
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.
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.

Experimental Design

ff2n	Two-level full factorial design.
fullfact	Full factorial design.
parseWilkinsonFormula	Parse and expand statistical model formulae using the Wilkinson notation.
sigma_pts	Calculates 2*N+1 sigma points in N dimensions.
x2fx	Convert predictors to design matrix.

Regression

CompactLinearModel	Compact linear regression model
CoxModel	Cox proportional hazards regression model class.
coxphfit	Fit a Cox proportional hazards regression model.
fitcox	Fit a Cox proportional hazards regression model.
fitglm	Fit a generalized linear regression model.
fitglme	Fit a generalized linear mixed-effects model specified by a formula.
fitlm	Fit a linear regression model to data and return a ‘LinearModel’ object.
fitlme	Fit a linear mixed-effects model specified by a formula.
fitlmematrix	Fit a linear mixed-effects model from design matrices.
fitnlm	Fit a nonlinear regression model.
GeneralizedLinearMixedModel	Generalized linear mixed-effects model fitted to data.
GeneralizedLinearModel	Generalized linear regression model class.
glmfit	Perform generalized linear model fitting.
glmval	Predict values for a generalized linear model.
invpred	Inverse prediction from a simple linear regression.
lasso	Lasso and elastic-net regularized least-squares regression.
lassoglm	Lasso and elastic-net regularized generalized linear model regression.
LinearFormula	Model formula of a linear or generalized linear regression.
LinearMixedModel	Linear mixed-effects model fitted to data.
LinearModel	Linear regression model
logistic_regression	Perform ordinal logistic regression.
mnrfit	Fit a multinomial logistic regression model.
mnrval	Predict values for a multinomial logistic regression model.
monotone_smooth	Produce a smooth monotone increasing approximation to a sampled functional dependence.
mvregress	Multivariate (multiple-response) linear regression by maximum likelihood.
mvregresslike	Negative log-likelihood for a multivariate regression model.
nlinfit	Fit a nonlinear regression model.
nlparci	Confidence intervals for the coefficients of a nonlinear regression.
nlpredci	Confidence intervals for predictions of a nonlinear regression.
NonLinearModel	Nonlinear regression model class.
plsregress	Calculate partial least squares regression using SIMPLS algorithm.
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.
robustfit	Robust linear regression.
stepwisefit	Perform stepwise linear regression using conditional p-value criteria.
stepwiseglm	Fit a generalized linear regression model by stepwise term selection.
stepwiselm	Fit a linear regression model using stepwise regression and return a ‘LinearModel’ object.

Supervised Learning

ClassificationDiscriminant	Discriminant analysis classification
ClassificationGAM	Generalized additive model classification
ClassificationKernel	Gaussian kernel binary classifier for large data.
ClassificationKNN	K-nearest neighbors classification
ClassificationLinear	Linear binary classifier for high dimensional data.
ClassificationNaiveBayes	Naive Bayes classification
ClassificationNeuralNetwork	Neural network classification
ClassificationPartitionedKernel	Cross-validated Gaussian kernel binary classifier.
ClassificationPartitionedLinear	Cross-validated linear binary classifier.
ClassificationPartitionedModel	Cross-validated classification model
ClassificationSVM	Support Vector Machine classification
CompactClassificationDiscriminant	Compact discriminant analysis classification
CompactClassificationGAM	Compact generalized additive model classification
CompactClassificationNaiveBayes	Compact naive Bayes classification
CompactClassificationNeuralNetwork	Compact neural network classification
CompactClassificationSVM	Compact Support Vector Machine classification
CompactRegressionGAM	Compact generalized additive model regression
CompactRegressionGP	Create a CompactRegressionGP object containing a Gaussian process regression model without its training data.
CompactRegressionNeuralNetwork	Create a CompactRegressionNeuralNetwork object, a neural network regression model that has dropped its training data.
CompactRegressionSVM	Create a CompactRegressionSVM object, a support vector regression model that has dropped its training data.
fcnnpredict	Make predictions from a fully connected Neural Network.
fcnntrain	Train a fully connected Neural Network.
fitcdiscr	Fit a Linear Discriminant Analysis classification model.
fitcgam	Fit a Generalized Additive Model (GAM) for binary classification.
fitckernel	Fit a Gaussian kernel binary classifier.
fitcknn	Fit a k-Nearest Neighbor classification model.
fitclinear	Fit a linear binary classifier.
fitcnb	Fit a naive Bayes classification model.
fitcnet	Fit a Neural Network classification model.
fitcsvm	Fit a Support Vector Machine classification model.
fitrgam	Fit a Generalized Additive Model (GAM) for regression.
fitrgp	Fit a Gaussian process regression model.
fitrkernel	Fit a Gaussian kernel regression model.
fitrlinear	Fit a linear regression model.
fitrnet	Fit a neural network regression model.
fitrsvm	Fit a support vector machine regression model.
gamboostinter	Boost trees over selected pairs of predictors.
gamboostpairs	Score every pair of predictors for an interaction.
gamboostpredict	Predict from a generalized additive model of boosted trees.
gamboosttrain	Fit a generalized additive model of boosted trees.
gampredict	Evaluate a generalized additive model on new data.
gamtrain	Fit a generalized additive model of smoothing splines.
RegressionGAM	Create a RegressionGAM class object containing a Generalized Additive Model (GAM) for regression.
RegressionGP	Create a RegressionGP object containing a Gaussian process regression model.
RegressionKernel	Gaussian kernel regression model for large data.
RegressionLinear	Linear regression model for high dimensional data.
RegressionNeuralNetwork	Create a RegressionNeuralNetwork object containing a neural network regression model.
RegressionPartitionedKernel	Cross-validated Gaussian kernel regression model.
RegressionPartitionedLinear	Cross-validated linear regression model.
RegressionPartitionedModel	Create a RegressionPartitionedModel object, a regression model cross validated over a partition of its training data.
RegressionSVM	Create a RegressionSVM object containing a support vector machine regression model.
svmpredict	This function predicts new labels from a testing instance matrix 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 matrix.

Clustering

CalinskiHarabaszEvaluation	Calinski-Harabasz clustering evaluation.
cluster	Define clusters from an agglomerative hierarchical cluster tree.
ClusterCriterion	A clustering evaluation object.
clusterdata	Wrapper function for ‘linkage’ and ‘cluster’. If
cophenet	Compute the cophenetic correlation coefficient.
DaviesBouldinEvaluation	Davies-Bouldin object to evaluate clustering solutions
dbscan	Density-Based Spatial Clustering of Applications with Noise (DBSCAN).
evalclusters	Create a clustering evaluation object to find the optimal number of clusters.
fitgmdist	Fit a Gaussian mixture model with K components to DATA.
GapEvaluation	Gap evaluation for clustering solutions
gmdistribution	Create an object of the gmdistribution class which represents a Gaussian mixture model with k components of n-dimensional Gaussians.
inconsistent	Compute the inconsistency coefficient for each link of a hierarchical cluster tree.
kmeans	Perform a K-means clustering of the N*D matrix DATA.
kmedoids	Partition observations into K clusters using the k-medoids algorithm.
linkage	Produce a hierarchical clustering dendrogram.
optimalleaforder	Compute the optimal leaf ordering of a hierarchical binary cluster tree.
SilhouetteEvaluation	Silhouette evaluation for clustering
spectralcluster	Partition observations into K clusters using spectral clustering.

Nearest Neighbors

createns	Create a nearest neighbor searcher object.
editDistance	Compute the edit (Levenshtein) distance between strings or documents.
ExhaustiveSearcher	Exhaustive nearest neighbor searcher
hnswSearcher	Hierarchical Navigable Small World (HNSW) nearest neighbor searcher class.
KDTreeSearcher	KD-tree nearest neighbor searcher
knnsearch	Find k-nearest neighbors from input data.
mahal	Mahalanobis' D-square distance.
pdist	Return the distance between any two rows in X.
pdist2	Compute pairwise distance between two sets of vectors.
rangesearch	Find all neighbors within specified distance from input data.
squareform	Interchange between distance matrix and distance vector formats.

Anomaly Detection

iforest	Detect anomalies with an isolation forest.
IsolationForest	Isolation Forest model for anomaly detection.
LocalOutlierFactor	Local Outlier Factor model for anomaly detection.
lof	Detect anomalies with the Local Outlier Factor (LOF) method.
ocsvm	Detect anomalies with a one-class support vector machine.
OneClassSVM	One-class support vector machine model for anomaly detection.
robustcov	Robust multivariate covariance and mean estimate.

Dimensionality Reduction

canoncorr	Canonical correlation analysis.
cmdscale	Classical multidimensional scaling of a matrix.
factoran	Common factor analysis.
mdscale	Nonclassical (metric and nonmetric) multidimensional scaling.
nnmf	Nonnegative matrix factorization.
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.
ppca	Probabilistic principal component analysis.
princomp	Performs a principal component analysis on a NxP data matrix X.
procrustes	Procrustes Analysis.
ReconstructionICA	Reconstruction independent component analysis (RICA) feature-extraction model.
rica	Reconstruction independent component analysis (RICA) for feature extraction.
rotatefactors	Rotate a factor-loading matrix.
sparsefilt	Sparse filtering for feature extraction.
SparseFiltering	Sparse filtering feature-extraction model.
tsne	t-distributed stochastic neighbor embedding (t-SNE).

Model Evaluation

confusionchart	Display a chart of a confusion matrix.
confusionmat	Compute a confusion matrix for classification problems
ConfusionMatrixChart	Confusion matrix chart for classification results
crossval	Perform cross validation on given data.
cvpartition	Partition data for cross-validation
perfcurve	Receiver operating characteristic (ROC) and other classifier performance curves.
rocmetrics	Receiver operating characteristic (ROC) metrics for classifier output.

Markov Models

hmmdecode	Posterior state probabilities of a hidden Markov model.
hmmestimate	Estimation of a hidden Markov model for a given sequence.
hmmgenerate	Output sequence and hidden states of a hidden Markov model.
hmmtrain	Estimate the parameters of a hidden Markov model from emitted sequences.
hmmviterbi	Viterbi path of a hidden Markov model.

Random Sampling

johnsrnd	Random arrays from the Johnson system of distributions.
mhsample	Draws NSAMPLES samples from a target stationary distribution PDF using Metropolis-Hastings algorithm.
pearsrnd	Random arrays from the Pearson system of distributions.
qrandn	Returns random deviates drawn from a q-Gaussian distribution.
slicesample	Draws NSAMPLES samples from a target stationary distribution PDF using slice sampling of Radford M.

Distribution Classes

paretotails	Piecewise distribution with generalized Pareto tails.
prob.ProbabilityDistribution	Abstract base class of the probability distribution objects.
prob.BetaDistribution	Beta probability distribution object.
prob.BinomialDistribution	Binomial probability distribution object.
prob.BirnbaumSaundersDistribution	Birnbaum-Saunders probability distribution object.
prob.BurrDistribution	Burr probability distribution object.
prob.ExponentialDistribution	Exponential probability distribution object.
prob.ExtremeValueDistribution	Extreme value probability distribution object.
prob.GammaDistribution	Gamma probability distribution object.
prob.GeneralizedExtremeValueDistribution	Generalized extreme value probability distribution object.
prob.GeneralizedParetoDistribution	Generalized Pareto probability distribution object.
prob.HalfNormalDistribution	Half-normal probability distribution object.
prob.InverseGaussianDistribution	Inverse Gaussian probability distribution object.
prob.KernelDistribution	Kernel probability distribution object.
prob.LogisticDistribution	Logistic probability distribution object.
prob.LoglogisticDistribution	Log-logistic probability distribution object.
prob.LognormalDistribution	Lognormal probability distribution object.
prob.LoguniformDistribution	Log-uniform probability distribution object.
prob.MultinomialDistribution	Multinomial probability distribution object.
prob.NakagamiDistribution	Nakagami probability distribution object.
prob.NegativeBinomialDistribution	Negative binomial probability distribution object.
prob.NormalDistribution	Normal probability distribution object.
prob.PiecewiseLinearDistribution	Piecewise linear probability distribution object.
prob.PoissonDistribution	Poisson probability distribution object.
prob.RayleighDistribution	Rayleigh probability distribution object.
prob.RicianDistribution	Rician probability distribution object.
prob.StableDistribution	Stable probability distribution object.
prob.tLocationScaleDistribution	Location-Scale Student's T probability distribution object.
prob.TriangularDistribution	Triangular probability distribution object.
prob.UniformDistribution	Continuous uniform probability distribution object.
prob.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.
copulafit	Fit a copula to data.
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	Estimate parameters and confidence intervals for the generalized extreme value (GEV) distribution.
gevlike	Negative log-likelihood for the generalized extreme value (GEV) distribution.
gevfit_lmom	Find an estimator (PARAMHAT) of the generalized extreme value (GEV) distribution fitting DATA using the method of L-moments.
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 Rician distribution.
ricelike	Negative log-likelihood for the Rician distribution.
stblfit	Estimate parameters and confidence intervals for the stable distribution.
stbllike	Negative log-likelihood for the stable 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 parameters 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.
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.
stblcdf	Stable cumulative distribution function (CDF).
stblinv	Inverse of the stable cumulative distribution function (iCDF).
stblpdf	Stable probability density function (PDF).
stblrnd	Random arrays from the stable 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.
copulaparam	Copula parameter as a function of rank correlation.
copulastat	Rank correlation for a copula family.
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.
mlecov	Asymptotic covariance matrix of maximum likelihood estimators.
pdf	Return the PDF of a univariate distribution evaluated at X.
random	Random arrays from a given one-, two-, or three-parameter distribution.

Plotting

andrewsplot	Create an Andrews plot of the multivariate data in X.
bar3	Plot a 3D bar graph.
bar3h	Plot a horizontal 3D bar graph.
biplot	Create a biplot of the coefficients in COEFS.
boxplot	Produce a box plot.
cdfplot	Display an empirical cumulative distribution function.
dendrogram	Plot a dendrogram of a hierarchical binary cluster tree.
ecdfhist	Create a histogram from the output of ‘ecdf’.
einstein	Plots the tiling of the basic clusters of einstein tiles.
glyphplot	Create a star (glyph) plot of the multivariate data in X.
gplotmatrix	Create a matrix of scatter plots grouped by a categorical variable.
gscatter	Draw a scatter plot with grouped data.
hist3	Produce bivariate (2D) histogram counts or plots.
histfit	Plot histogram with superimposed distribution fit.
manovacluster	Cluster group means using manova1 output.
normplot	Produce normal probability plot of the data in X.
parallelcoords	Create a parallel coordinates plot of the multivariate data in X.
ppplot	Perform a PP-plot (probability plot).
probplot	Produce a probability plot of the data in Y against the distribution DIST.
qqplot	Perform a QQ-plot (quantile plot).
scatterhist	Create a scatter plot of X and Y with marginal histograms.
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.

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.

Utilities

cholcov	Cholesky-like decomposition for covariance matrix.
logit	Compute the logit for each value of P
makima	Compute the 1-D Modified Akima piecewise cubic Hermite interpolant of sample data X and Y.
probit	Probit transformation
statget	Read one option out of a statistics options structure.
statset	Create or modify an options structure for iterative statistics algorithms.