cprob: Extract Contour Probabilities In R2BayesX: Estimate Structured Additive Regression Models with 'BayesX'

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

 `1` ```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.

Author(s)

Nikolaus Umlauf, Thomas Kneib, Stefan Lang, Achim Zeileis.

References

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

`bayesx`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22``` ```## 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) ```