Description Usage Arguments Examples
This function plot posterior distributions of the parameters.
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chains |
Gibbs sampling chains |
trueValues |
numeric vector of true values |
outline |
logical value whether showing outliers |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 | 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)
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