riskplot {CoMiRe} | R Documentation |
Additional risk function plot
Description
Posterior mean (continuous lines) and pointwise credible bands (shaded areas) for Ra(x, a)
.
Usage
riskplot(risk.data, xlab = NULL, x = NULL, ylim=c(0,1), xlim=c(0, max(x)))
Arguments
risk.data |
output of |
xlab |
the title of the x axis. |
x |
numeric vector for the covariate relative to the dose of exposure used in |
xlim , ylim |
numeric vectors of length 2, giving the x and y coordinates ranges for the plot. |
Author(s)
Antonio Canale
Examples
{
data(CPP)
attach(CPP)
n <- NROW(CPP)
J <- H <- 10
premature <- as.numeric(gestage<=37)
mcmc <- list(nrep=5000, nb=2000, thin=5, ndisplay=4)
## too few iterations to be meaningful. see below for safer and more comprehensive results
mcmc <- list(nrep=10, nb=2, thin=1, ndisplay=4)
prior <- list(mu.theta=mean(gestage), k.theta=10, eta=rep(1, J)/J,
alpha=rep(1,H)/H, a=2, b=2, J=J, H=H)
fit.dummy <- comire.gibbs(gestage, dde, family="continuous",
mcmc=mcmc, prior=prior, seed=1, max.x=180)
risk.data <- add.risk(y = gestage, x = dde, fit = fit.dummy, mcmc = mcmc,
a = 37, x.grid = seq(0, max(dde), length = 100))
riskplot(risk.data$summary.risk, xlab="DDE", x = dde, xlim = c(0,150))
## safer procedure with more iterations (it may take some time)
mcmc <- list(nrep=5000, nb=2000, thin=5, ndisplay=4)
## Fit the model for continuous y
prior <- list(mu.theta=mean(gestage), k.theta=10, eta=rep(1, J)/J,
alpha=rep(1,H)/H, a=2, b=2, J=J, H=H)
fit <- comire.gibbs(gestage, dde, family="continuous",
mcmc=mcmc, prior=prior, seed=5, max.x=180)
risk.data <- add.risk(y = gestage, x = dde, fit = fit, mcmc = mcmc,
a = 37, x.grid = seq(0, max(dde), length = 100))
riskplot(risk.data$summary.risk, xlab="DDE",
x = dde, xlim = c(0,150))
}
[Package CoMiRe version 0.8 Index]