# summary.bayesx

##### Bayesx Summary Statistics

Takes an object of class `"bayesx"`

and displays summary statistics.

- Keywords
- regression

##### Usage

```
# S3 method for 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.

##### See Also

##### Examples

```
# 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)
# }
```

*Documentation reproduced from package R2BayesX, version 1.1-1, License: GPL-2 | GPL-3*