# summary.bayesx: Bayesx Summary Statistics In R2BayesX: Estimate Structured Additive Regression Models with 'BayesX'

## Description

Takes an object of class `"bayesx"` and displays summary statistics.

## Usage

 ```1 2 3``` ```## S3 method for class 'bayesx' summary(object, model = NULL, digits = max(3, getOption("digits") - 3), ...) ```

## Arguments

 `object` an object of class `"bayesx"`. `model` for which model the plot should be provided, either an integer or a character, e.g. `model = "mcmc.model"`. `digits` choose the decimal places of represented numbers in the summary statistics. `...` not used.

## Details

This function supplies detailed summary statistics of estimated objects with BayesX, i.e. informations on smoothing parameters or variances are supplied, as well as random effects variances and parametric coefficients. Depending on the model estimated and the output provided, additional model specific information will be printed, e.g. if `method = "MCMC"` was specified in `bayesx`, the number of `iterations`, the `burnin` and so forth is shown. Also goodness of fit statistics are provided if the `object` contains such informations.

## Author(s)

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

`bayesx`, `read.bayesx.output`.
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21``` ```## Not run: ## generate some data set.seed(111) n <- 500 ## regressors dat <- data.frame(x = runif(n, -3, 3), z = runif(n, -3, 3), w = runif(n, 0, 6), fac = factor(rep(1:10, n/10))) ## response dat\$y <- with(dat, 1.5 + sin(x) + cos(z) * sin(w) + c(2.67, 5, 6, 3, 4, 2, 6, 7, 9, 7.5)[fac] + rnorm(n, sd = 0.6)) ## estimate model b <- bayesx(y ~ sx(x) + sx(z, w, bs = "te") + fac, data = dat, method = "MCMC") ## now show summary statistics summary(b) ## End(Not run) ```