1d:T7b2,# Mixtures of SAL Distributions The current version of the MixSAL package allows users to generate data from a multivariate SAL distribution or a mixture of multivariate SAL distributions, evaluate the probability density function of a multivariate SAL distribution or a mixture of multivariate SAL distributions, and fit a mixture of multivariate SAL distributions using the Expectation-Maximization (EM) algorithm (see Franczak et. al, 2014 for details). package ## Details ||| |:--|:--| |Package:|MixSAL| |Type:|Package| |Version:|1.0| |Date:|2018-05-09| |License:|GPL (>=3.1.3)| This package contains the function msal for carrying about model based clustering using mixtures of SAL distributions; the functions rsal and rmsal for generating data from a multivariate SAL or mixture of multivariate SAL distributions, and hte functions dsal and dmsal for evaluating the model based clustering and classification using the mixture of generalized hyperbolic factor analyzers; the function MCGHD for model based clustering using the mixture of coalesced generalized hyperbolic distributions, and some real data sets. ## Author(s) Brian C. Franczak [aut, cre], Ryan P. Brown [aut, ctb], and Paul D. McNicholas [aut, ctb] Maintainer: Brian C. Franczak ## References Franczak et. al (2014). Mixtures of Shifted Asymmetric Laplace Distributions. IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(6), 1149-1157. ## Examples ```r ## Clustering Simulated Data alpha <- matrix(c(2,2,1,2),2,2) sig <- array(NA,dim=c(2,2,2)) sig[,,1] <- diag(2) sig[,,2] <- matrix(c(1,0.5,0.5,1),2,2) mu <- matrix(c(0,0,-2,5),2,2) pi.g <- rep(1/2,2) x <- rmsal(n=500,p=2,alpha=alpha,sig=sig,mu=mu,pi.g=pi.g) msal.ex1 <- msal(x=x[,-1],G=2) table(x[,1],msal.ex1$cluster) ## Evaluate the probability density function of the specified mixture of SAL distributions pdf.sal <- dmsal(x=x[,-1],alpha=alpha,sig=sig,mu=mu,pi.g=pi.g) pdf.sal[1:10] ```

MixSAL-package