plotPost: Plot Posterior Distributions

In phenoCDM: Continuous Development Models for Incremental Time-Series Analysis

Description

This function plot posterior distributions of the parameters.

Usage

plotPost(chains, trueValues = NULL, outline = FALSE)

Arguments

chains	Gibbs sampling chains
trueValues	numeric vector of true values
outline	logical value whether showing outliers

Examples

ssSim <- phenoSim(nSites = 2, #number of sites
                  nTSet = 30, #number of Time steps
                  beta = c(1, 2), #beta coefficients
                  sig = .01, #process error
                  tau = .1, #observation error
                  plotFlag = TRUE, #whether plot the data or not
                  miss = 0.05, #fraction of missing data
                  ymax = c(6, 3) #maximum of saturation trajectory
)

ssOut <- fitCDM(x = ssSim$x, #predictors
                nGibbs = 200,
                nBurnin = 100,
                z = ssSim$z,#response
                connect = ssSim$connect, #connectivity of time data
                quiet=TRUE)

summ <- getGibbsSummary(ssOut, burnin = 100, sigmaPerSeason = FALSE)

colMeans(summ$ymax)
colMeans(summ$betas)
colMeans(summ$tau)
colMeans(summ$sigma)

par(mfrow = c(1,3), oma = c(1,1,3,1), mar=c(2,2,0,1), font.axis=2)

plotPost(chains = ssOut$chains[,c("beta.1", "beta.2")], trueValues = ssSim$beta)
plotPost(chains = ssOut$chains[,c("ymax.1", "ymax.2")], trueValues = ssSim$ymax)
plotPost(chains = ssOut$chains[,c("sigma", "tau")], trueValues = c(ssSim$sig, ssSim$tau))

mtext('Posterior distributions of the parameters', side = 3, outer = TRUE, line = 1, font = 2)
legend('topleft', legend = c('posterior', 'true value'), col = c('black', 'red'),
         lty = 1, bty = 'n', cex=1.5, lwd =2)

phenoCDM documentation built on May 1, 2019, 9:26 p.m.