R2BayesX (version 1.0-0)

cprob: Extract Contour Probabilities

Description

Function to extract estimated contour probabilities of a particular effect estimated with P-splines using Markov chain Monte Carlo (MCMC) estimation techniques. Note that, the contour probability option must be specified within function sx, see the example.

Usage

cprob(object, model = NULL, term = NULL, ...)

Arguments

object

an object of class "bayesx".

model

for which model the contour probabilities should be provided, either an integer or a character, e.g. model = "mcmc.model".

term

if not NULL, the function will search for the term contour probabilities should be extracted for, either an integer or a character, eg term = "s(x)".

...

not used.

References

Brezger, A., Lang, S. (2008): Simultaneous probability statements for Bayesian P-splines. Statistical Modeling, 8, 141--186.

See Also

bayesx.

Examples

## Not run: 
# ## generate some data
# set.seed(111)
# n <- 500
# 
# ## regressor
# dat <- data.frame(x = runif(n, -3, 3))
# 
# ## response 
# dat$y <- with(dat, 1.5 + sin(x) + rnorm(n, sd = 0.6))
# 
# ## estimate model
# ## need to set the contourprob option, 
# ## otherwise BayesX will not calculate probabilities
# ## see also the reference manual of BayesX available
# ## at www.BayesX.org
# b <- bayesx(y ~ sx(x, bs = "ps", contourprob = 4), data = dat)
# 
# ## extract contour probabilities
# cprob(b, term = "sx(x)")
# ## End(Not run)