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.

1 |

`object` |
an object of class |

`model` |
for which model the contour probabilities should be provided, either an integer or a
character, e.g. |

`term` |
if not |

`...` |
not used. |

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

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

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)
``` |

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