# summary.bayesx

0th

Percentile

##### 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.

bayesx, read.bayesx.output.

##### Aliases
• summary.bayesx
##### 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

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