Nothing
plot.bkpc <-
function(x, type = "default", n.burnin = 0, ...){
n.samples <- dim(x$beta)[1]
if (n.burnin >= n.samples) stop("error: too many burn-in iterations specified")
if (n.burnin < 0) n.burnin <- 0
if (type == "tracePlot"){
matplot(x$beta[(n.burnin + 1) : n.samples, ], main = expression(beta), ylab = "", xlab = "Iterations", type='l', ...)
matplot(x$tau[(n.burnin + 1) : n.samples, ], main = expression(tau), ylab = "", xlab = "Iterations", type='l', ...)
matplot(x$z[(n.burnin + 1) : n.samples, ], main = "z", xlab = "Iterations", ylab = "", type='l', ...)
plot(x$sigmasq[(n.burnin + 1) : n.samples,1, drop = FALSE], main = expression(sigma^2), ylab = "", xlab = "Iterations", type='l', ...)
}
else if (type == "default"){
plot(apply(x$beta[(n.burnin + 1) : n.samples, ], 2, median), pch = 20, xlab = "", ylab = expression(beta),
ylim = c(min(x$beta[(n.burnin + 1) : n.samples, ]), max(x$beta[(n.burnin + 1) : n.samples, ])), col = 2)
u <- apply(x$beta[(n.burnin + 1) : n.samples, ], 2, quantile, probs = c(0.9))
l <- apply(x$beta[(n.burnin + 1) : n.samples, ], 2, quantile, probs = c(0.1))
for(i in 1 : dim(x$beta)[2])lines(c(i, i), c(l[i], u[i]), ...)
abline(h = 0)
u <- apply(x$tau[(n.burnin + 1) : n.samples, ], 2, quantile, probs = c(0.9))
l <- apply(x$tau[(n.burnin + 1) : n.samples, ], 2, quantile, probs = c(0.1))
plot(apply(x$tau[(n.burnin + 1) : n.samples, ], 2, median), pch = 20, xlab = "", ylab = expression(tau),
ylim = c(min(x$tau[(n.burnin + 1) : n.samples, ]), max(x$tau[(n.burnin + 1) : n.samples, ])), col = 2)
for(i in 1 : dim(x$tau)[2])lines(c(i, i), c(l[i], u[i]), ...)
u <- apply(x$z[(n.burnin + 1) : n.samples, ], 2, quantile, probs = c(0.9))
l <- apply(x$z[(n.burnin + 1) : n.samples, ], 2, quantile, probs = c(0.1))
plot(apply(x$z[(n.burnin + 1) : n.samples, ], 2, median), pch = 20, xlab = "", ylab = expression(z),
ylim = c(min(x$z[(n.burnin + 1) : n.samples, ]), max(x$z[(n.burnin + 1) : n.samples, ])), col = 2)
for(i in 1 : dim(x$z)[2])lines(c(i, i), c(l[i], u[i]), ...)
plot(apply(x$sigmasq[(n.burnin + 1) : n.samples,1, drop = FALSE], 2, median), pch = 20, xlab = "", ylab = expression(sigma^2),
ylim = c(min(x$sigmasq[(n.burnin + 1) : n.samples,1, drop = FALSE]), max(x$sigmasq[(n.burnin + 1) : n.samples, 1, drop = FALSE])), col = 2)
lines(c(1, 1), c(apply(x$sigmasq[(n.burnin + 1) : n.samples, 1, drop = FALSE], 2, quantile, probs = c(0.1)),
apply(x$sigmasq[(n.burnin + 1) : n.samples, 1, drop = FALSE], 2, quantile, probs = c(0.9))), ...)
}
else if (type == "boxPlot"){
boxplot(x$beta[(n.burnin + 1) : n.samples, ], ylab = expression(beta), ...)
boxplot(x$tau[(n.burnin + 1) : n.samples, ], main = expression(tau), ...)
boxplot(x$z[(n.burnin + 1) : n.samples, ], ylab = "z", ...)
boxplot(x$sigmasq[(n.burnin + 1) : n.samples, 1, drop = FALSE], ylab = expression(sigma^2), ...)
}
else stop("error: Plot type not supported for a bkpc object")
}
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.