## ----setup, include=FALSE----------------------------------------------------- knitr::opts_chunk$set(fig.width=7, fig.height = 5, fig.align = 'center', fig.show='hold', warning=FALSE, message=FALSE, progress=FALSE, collapse=TRUE, comment="#>") if(isTRUE(capabilities("cairo"))) { knitr::opts_chunk$set(dev.args=list(type="cairo")) } ## ----eval=FALSE--------------------------------------------------------------- # install.packages('devtools') # devtools::install_github('Keefe-Murphy/IMIFA') ## ----eval=FALSE--------------------------------------------------------------- # install.packages('IMIFA') ## ----------------------------------------------------------------------------- library(IMIFA) ## ----eval=FALSE--------------------------------------------------------------- # # Simulate 100 observations from 3 balanced clusters with cluster-specific numbers of latent factors # sim_data <- sim_IMIFA_data(N=100, G=3, P=20, Q=c(2, 2, 5), # psi=matrix(rgamma(60, 2, 1), nrow=20, ncol=3), # mu=matrix(rnorm(60, -2 + 1:3, 1), nrow=20, ncol=3, byrow=TRUE)) ## ----------------------------------------------------------------------------- data(olive) ## ----eval=FALSE--------------------------------------------------------------- # ?olive ## ----eval=FALSE--------------------------------------------------------------- # ?mcmc_IMIFA ## ----eval=FALSE--------------------------------------------------------------- # simMFA <- mcmc_IMIFA(olive, method="MFA", n.iters=10000, range.G=3:6, range.Q=0:3, centering=FALSE, # scaling="unit", uni.type="isotropic", score.switch=FALSE) ## ----eval=FALSE--------------------------------------------------------------- # simMIFA <- mcmc_IMIFA(olive, method="MIFA", n.iters=10000, centering=TRUE, # range.G=1:3, z.init="kmeans") ## ----eval=FALSE--------------------------------------------------------------- # simOMIFA <- mcmc_IMIFA(olive, method="OMIFA", n.iters=10000, range.G=10, learn.alpha=TRUE, # nu=3, alpha.d1=3.5, alpha.d2=7, prop=0.8, epsilon=0.01) ## ----eval=FALSE--------------------------------------------------------------- # simIMIFA <- mcmc_IMIFA(olive, method="IMIFA", n.iters=50000, verbose=FALSE) ## ----eval=FALSE--------------------------------------------------------------- # resMFA <- get_IMIFA_results(simMFA) ## ----eval=FALSE--------------------------------------------------------------- # resMFA2 <- get_IMIFA_results(simMFA, G=3, criterion="aic.mcmc") ## ----eval=FALSE--------------------------------------------------------------- # resIMIFA <- get_IMIFA_results(simIMIFA, z.avgsim=TRUE) ## ----include=FALSE------------------------------------------------------------ load(file="res_olive_IMIFA__Edited-Vignette-only-Version.rda") ## ----------------------------------------------------------------------------- summary(resIMIFA, MAP=TRUE) ## ----results='hide', eval=FALSE----------------------------------------------- # plot(resIMIFA, plot.meth="GQ") ## ----results='hide', echo=FALSE----------------------------------------------- plot(resIMIFA, plot.meth="GQ", g=1) ## ----results='hide', echo=FALSE----------------------------------------------- suppressWarnings(plot(resIMIFA, plot.meth="GQ", g=2)) ## ----results='hide', echo=FALSE----------------------------------------------- plot(resIMIFA, plot.meth="GQ", g=3) ## ----------------------------------------------------------------------------- plot(resIMIFA, plot.meth="zlabels", zlabels=olive$area, g=1) ## ----results="hide"----------------------------------------------------------- plot(resIMIFA, plot.meth="zlabels", zlabels=olive$area, g=2) ## ----results="hide"----------------------------------------------------------- plot(resIMIFA, plot.meth="zlabels", g=4) ## ----eval=FALSE--------------------------------------------------------------- # plot(resIMIFA, plot.meth="zlabels", g=5) ## ----results='hide', echo=FALSE----------------------------------------------- suppressMessages(plot(resIMIFA, plot.meth="zlabels", g=5)) ## ----------------------------------------------------------------------------- plot(resIMIFA, plot.meth="means", param="means", mat=TRUE, g=1) ## ----eval=FALSE--------------------------------------------------------------- # plot(resIMIFA, plot.meth="trace", param="scores", mat=TRUE, ind=1) ## ----eval=FALSE--------------------------------------------------------------- # plot(resIMIFA, plot.meth="trace", param="scores", mat=TRUE, by.fac=TRUE, fac=2) ## ----------------------------------------------------------------------------- plot(resIMIFA, plot.meth="means", param="loadings", heat.map=TRUE, g=1) ## ----------------------------------------------------------------------------- plot(resIMIFA, plot.meth="parallel.coords", param="uniquenesses") ## ----------------------------------------------------------------------------- plot(resIMIFA, plot.meth="errors", g=1) ## ----------------------------------------------------------------------------- plot(resIMIFA, plot.meth="errors", g=3) ## ----fig.height=7------------------------------------------------------------- plot(resIMIFA, plot.meth="all", param="alpha") ## ----fig.height=7------------------------------------------------------------- plot(resIMIFA, plot.meth="all", param="discount", partial=TRUE)