Contents.m

% PROBABILITY DISTRIBUTION FUNCTIONS (in the dist-folder):
%
% Priors 
%   PRIOR_FIXED       Fix parameter to its current value
%   PRIOR_GAMMA       Gamma prior structure     
%   PRIOR_GAUSSIAN    Gaussian prior structure     
%   PRIOR_INVGAMMA    Inverse-gamma prior structure     
%   PRIOR_INVT        Inverse Student-t prior structure
%   PRIOR_INVUNIF     Inverse uniform prior structure
%   PRIOR_LAPLACE     Laplace (double exponential) prior structure
%   PRIOR_LOGGAUSSIAN Log-Gaussian prior structure     
%   PRIOR_LOGLOGUNIF  Uniform prior structure for the log(log(parameter))
%   PRIOR_LOGT        Student-t prior structure for the logarithm of the parameter
%   PRIOR_LOGUNIF     Uniform prior structure for the logarithm of the parameter
%   PRIOR_SINVCHI2    Scaled inverse-chi-square prior structure
%   PRIOR_SQINVGAMMA  Gamma prior structure for square inverse of the parameter
%   PRIOR_SQINVLOGUNIF Uniform prior structure for the log of the square 
%                      inverse of parameter
%   PRIOR_SQINVSINVCHI2 Scaled-Inv-Chi^2 prior structure for square inverse 
%                       of the parameter
%   PRIOR_SQINVUNIF   Uniform prior structure for the square inverse of the 
%                     parameter
%   PRIOR_SQRTINVT    Student-t prior structure for the square root of
%                     inverse of the parameter
%   PRIOR_INVSQRTUNIF Uniform prior structure for the square root of 
%                     inverse of the parameter
%   PRIOR_SQRTT       Student-t prior structure for the square root of the
%                     parameter
%   PRIOR_SQRTUNIF    Uniform prior structure for the square root of the
%                     parameter
%   PRIOR_T           Student-t prior structure
%   PRIOR_UNIF        Uniform prior structure     
%
% Probability (log/cumulative) density functions
%   BETA_CDF      - Beta cumulative distribution function
%   BETA_INV      - Inverse of the beta cumulative distribution function (cdf)
%   BETA_LPDF     - Beta log-probability density function (lpdf)
%   BETA_PDF      - Beta probability density function (pdf)
%   DIR_LPDF      - Log probability density function of uniform Dirichlet
%                   distribution
%   DIR_PDF       - Probability density function of uniform Dirichlet
%                   distribution
%   GAM_CDF       - Cumulative of Gamma probability density function (cdf)
%   GAM_LPDF      - Log of Gamma probability density function (lpdf)
%   GAM_PDF       - Gamma probability density function (pdf)
%   GEO_LPDF      - Geometric log probability density function (lpdf)
%   INVGAM_LPDF   - Inverse-Gamma log probability density function
%   INVGAM_PDF    - Inverse-Gamma probability density function
%   LAPLACE_LPDF  - Laplace log-probability density function (lpdf)
%   LAPLACE_PDF   - Laplace probability density function (pdf)
%   LOGN_LPDF     - Log normal log-probability density function (lpdf)
%   LOGT_LPDF     - Log probability density function (lpdf) for log Student's T
%   MNORM_LPDF    - Multivariate-Normal log-probability density function (lpdf)
%   MNORM_PDF     - Multivariate-Normal log-probability density function (lpdf)
%   NBIN_CDF      - Negative binomial cumulative distribution function (cdf)
%   NBIN_INV      - Inverse of Negative binomial cumulative distribution function (inv)
%   NBIN_PDF      - Negative binomial probability density function (pdf)
%   NEGBIN_LPDF   - Negative binomial log probability density function
%   NEGBIN_PDF    - Negative binomial probability density function
%   NEGBINZTR_LPDF - Zero trunc. negative binomial log probability density function
%   NEGBINZTR_PDF - Zero trunc. negative binomial log probability density function
%   NORM_CDF      - Normal cumulative probability density function (cdf)
%   NORM_INV      - Inverse of the normal cumulative distribution function (cdf)
%   NORM_LPDF     - Normal log-probability density function (lpdf)
%   NORM_PDF      - Normal probability density function (pdf)
%   POISS_LPDF    - Poisson log-probability density function
%   POISS_PDF     - Poisson probability density function
%   SINVCHI2_LPDF - Scaled inverse-chi log-probability density function
%   SINVCHI2_PDF  - Scaled inverse-chi probability density function
%   T_CDF         - Student's t cumulative distribution function (cdf)
%   T_INV         - Inverse of Student's T cumulative distribution function (cdf)
%   T_LPDF        - Student's T log-probability density function (lpdf)
%   T_PDF         - Student's T probability density function (pdf)
%
% Random numbers
%   BETARAND      - Random matrices from beta distribution
%   CATRAND       - Random matrices from categorical distribution
%   DIRRAND       - Uniform dirichlet random vectors
%   EXPRAND       - Random matrices from exponential distribution
%   GAMRAND       - Random matrices from gamma distribution
%   GAMRAND1      - Random matrices from gamma distribution (mex)
%   INTRAND       - Random matrices from uniform integer distribution
%   INVGAMRAND    - Random matrices from inverse gamma distribution
%   INVGAMRAND1   - Random matrices from inverse gamma distribution (mex)
%   INVWISHRND    - Random matrices from inverse Wishart distribution
%   NORMLTRAND    - Random draws from a left-truncated normal
%                   distribution, with mean = mu, variance = sigma2
%   NORMRTRAND    - Random draws from a right-truncated normal
%                   distribution, with mean = mu, variance = sigma2
%   NORMTRAND     - Random draws from a normal truncated to interval
%   NORMTZRAND    - Random draws from a normal distribution truncated by zero
%   SINVCHI2RAND  - Random matrices from scaled inverse-chi distribution
%   TRAND         - Random numbers from Student's t-distribution
%   UNIFRAND      - Generate unifrom random numberm from interval [A,B]
%   WISHRND       - Random matrices from Wishart distribution
%
% Others
%   HAMMERSLEY    - Hammersley quasi-random sequence
%