Nothing
## ---- echo = F----------------------------------------------------------------
mycol<-c("#ee204d", "#1f75fe", "#1cac78", "#ff7538", "#b4674d", "#926eae",
"#fce883", "#000000", "#78dbe2", "#6e5160", "#ff43a4")
## -----------------------------------------------------------------------------
suppressPackageStartupMessages(require(DrBats))
set.seed = 45
toydata <- drbats.simul(N = 5,
P = 150,
t.range = c(0, 1000),
b.range = c(0.2, 0.4),
c.range = c(0.6, 0.8),
b.sd = 5,
c.sd = 5,
y.range = c(-5, 5),
sigma2 = 0.2,
breaks = 8,
data.type = 'sparse.tend')
## -----------------------------------------------------------------------------
matplot(t(toydata$t), t(toydata$X), type = 'l', lty = 1, lwd = 1,
xlab = 'Time', ylab = ' ')
points(t(toydata$t), t(toydata$X), pch = '.')
## -----------------------------------------------------------------------------
barplot(toydata$proj.pca$lambda.perc, ylim = c(0, 1),
col = mycol[1:length(toydata$proj.pca$lambda.perc)])
## ---- echo = F----------------------------------------------------------------
print(paste("Number of retained axes: ", toydata$wlu$D, sep = ""))
## ---- eval = F----------------------------------------------------------------
# fit <- modelFit(model = "PLT", var.prior = "IG", prog = "stan", Xhisto = toydata$Y.simul$Y,
# nchains = 4, nthin = 50, niter = 10000, D = toydata$wlu$D)
## ---- echo = F----------------------------------------------------------------
data("toydata")
data("stanfit")
## ---- echo = F----------------------------------------------------------------
codafit <- coda.obj(stanfit)
## -----------------------------------------------------------------------------
post <- postdens(codafit, Y = toydata$Y.simul$Y, D = toydata$wlu$D, chain = 1)
hist(post, main = "Histogram of the posterior density", xlab = "Density")
## -----------------------------------------------------------------------------
beta.res <- visbeta(codafit, toydata$Y.simul$Y, toydata$wlu$D, chain = 1, axes = c(1, 2), quant = c(0.05, 0.95))
ggplot2::ggplot() +
ggplot2::geom_path(data = beta.res$contour.df, ggplot2::aes(x = x, y = y, colour = ind)) +
ggplot2::geom_point(data = beta.res$mean.df, ggplot2::aes(x = x, y = y, colour = ind)) +
ggplot2::ggtitle("Convex hull of Score Estimates")
## -----------------------------------------------------------------------------
W.res <- visW(codafit, toydata$Y.simul$Y, toydata$wlu$D, chain = 1, factors = c(1, 2))
W.df <- data.frame(time = 1:9, W.res$res.W)
ggplot2::ggplot() +
ggplot2::geom_step(data = W.df, ggplot2::aes(x = time, y = Estimation, colour = Factor)) +
ggplot2::geom_step(data = W.df, ggplot2::aes(x = time, y = Lower.est, colour = Factor), linetype = 3) +
ggplot2::geom_step(data = W.df, ggplot2::aes(x = time, y = Upper.est, colour = Factor), linetype = 3) +
ggplot2::ggtitle("Latent Factor Estimations")
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