chi2stat copulastat evstat expstat fstat gamstat geostat gevstat gpstat hygestat lognstat nbinstat ncfstat nctstat ncx2stat normstat poisstat raylstat tstat unidstat unifstat wblstat
Chi-square mean and variance Copula rank correlation
Extreme value mean and variance Exponential mean and variance
F mean and variance Gamma mean and variance Geometric mean and variance
Generalized extreme value mean and variance Generalized Pareto mean and variance Hypergeometric mean and variance Lognormal mean and variance
Negative binomial mean and variance Noncentral F mean and variance Noncentral t mean and variance
Noncentral chi-square mean and variance Normal mean and variance Poisson mean and variance Rayleigh mean and variance Student's t mean and variance Discrete uniform mean and variance Continuous uniform mean and variance Weibull mean and variance
Distribution Fitting
Supported Distributions Piecewise Distributions Supported Distributions betafit binofit copulafit copulaparam dfittool evfit expfit
Beta parameter estimates Binomial parameter estimates Fit copula to data
Copula parameters as function of rank correlation Interactive distribution fitting Extreme value parameter estimates Exponential parameter estimates
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fit Gaussian mixture parameter estimates (gmdistribution) gamfit gevfit gpfit histfit johnsrnd lognfit mle mlecov nbinfit normfit normplot pearsrnd poissfit raylfit unifit wblfit wblplot
Gamma parameter estimates
Generalized extreme value parameter estimates Generalized Pareto parameter estimates Histogram with normal fit Johnson system random numbers Lognormal parameter estimates Maximum likelihood estimates
Asymptotic covariance of maximum likelihood estimators
Negative binomial parameter estimates Normal parameter estimates Normal probability plot Pearson system random numbers Poisson parameter estimates Rayleigh parameter estimates
Continuous uniform parameter estimates Weibull parameter estimates Weibull probability plot
Piecewise Distributions
boundary Piecewise distribution boundaries (piecewisedistribution) lowerparams (paretotails)
Lower Pareto tails parameters
nsegments Number of segments (piecewisedistribution) paretotails
Construct Pareto tails object
piecewisedistribution Create piecewise distribution object segment Segments containing values (piecewisedistribution) upperparams (paretotails)
Upper Pareto tails parameters
Negative Log-Likelihood
betalike evlike
Beta negative log-likelihood
Extreme value negative log-likelihood
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explike gamlike gevlike gplike lognlike mvregresslike normlike wbllike
Exponential negative log-likelihood Gamma negative log-likelihood
Generalized extreme value negative log-likelihood Generalized Pareto negative log-likelihood Lognormal negative log-likelihood
Negative log-likelihood for multivariate regression Normal negative log-likelihood Weibull negative log-likelihood
Random Number Generators
betarnd binornd chi2rnd copularnd datasample evrnd exprnd frnd gamrnd geornd gevrnd gprnd hygernd iwishrnd johnsrnd lhsdesign lhsnorm lognrnd mhsample mnrnd mvnrnd mvtrnd nbinrnd ncfrnd nctrnd ncx2rnd
Beta random numbers Binomial random numbers Chi-square random numbers Copula random numbers
Randomly sample from data, with or without replacement
Extreme value random numbers Exponential random numbers
F random numbers Gamma random numbers Geometric random numbers
Generalized extreme value random numbers Generalized Pareto random numbers Hypergeometric random numbers Inverse Wishart random numbers Johnson system random numbers Latin hypercube sample
Latin hypercube sample from normal distribution Lognormal random numbers Metropolis-Hastings sample Multinomial random numbers
Multivariate normal random numbers Multivariate t random numbers Negative binomial random numbers Noncentral F random numbers Noncentral t random numbers
Noncentral chi-square random numbers
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normrnd pearsrnd poissrnd randg random
Normal random numbers
Pearson system random numbers Poisson random numbers Gamma random numbers Random numbers
random (gmdistribution) Random numbers from Gaussian mixture
distribution random Random numbers from piecewise distribution (piecewisedistribution) randsample randtool raylrnd slicesample trnd unidrnd unifrnd wblrnd wishrnd
Random sample
Interactive random number generation Rayleigh random numbers Slice sampler
Student's t random numbers Discrete uniform random numbers Continuous uniform random numbers Weibull random numbers Wishart random numbers
Quasi-Random Numbers
addlistener (qrandstream) delete
(qrandstream) end (qrandset) findobj
(qrandstream) findprop
(qrandstream)
Add listener for event Delete handle object
Last index in indexing expression for point set Find objects matching specified conditions Find property of MATLAB handle object
eq (qrandstream) Test handle equality
ge (qrandstream) Greater than or equal relation for handles gt (qrandstream) Greater than relation for handles haltonset isvalid
(qrandstream)
Construct Halton quasi-random point set Test handle validity
le (qrandstream) Less than or equal relation for handles length (qrandset) Length of point set
lt (qrandstream) Less than relation for handles
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ndims (qrandset) Number of dimensions in matrix ne (qrandstream) Not equal relation for handles net (qrandset) notify
(qrandstream) qrand
(qrandstream) qrandset qrandstream reset
(qrandstream) scramble (qrandset) size (qrandset) sobolset
Generate quasi-random point set Notify listeners of event
Generate quasi-random points from stream Abstract quasi-random point set class Construct quasi-random number stream Reset state
Scramble quasi-random point set Number of dimensions in matrix
Construct Sobol quasi-random point set
rand (qrandstream) Generate quasi-random points from stream
Piecewise Distributions
boundary Piecewise distribution boundaries (piecewisedistribution) cdf Cumulative distribution function for piecewise (piecewisedistribution) distribution icdf Inverse cumulative distribution function for (piecewisedistribution) piecewise distribution lowerparams (paretotails)
Lower Pareto tails parameters
nsegments Number of segments (piecewisedistribution) paretotails
Construct Pareto tails object
pdf Probability density function for piecewise (piecewisedistribution) distribution piecewisedistribution Create piecewise distribution object random Random numbers from piecewise distribution (piecewisedistribution)
segment Segments containing values (piecewisedistribution) upperparams (paretotails)
Upper Pareto tails parameters
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