give.summary: Brief summary for the chain(s) obtained using the MCMC.

In bayesSurv: Bayesian Survival Regression with Flexible Error and Random Effects Distributions

Brief summary for the chain(s) obtained using the MCMC.

Description

This function computes a sample mean, quantiles and a Bayesian p-value which is defined as

p = 2\times\min(n_{-},\,n_{+}),

where n_{-} is the number of the sampled values which are negative and n_{+} is the number of sampled values which are positive.

Usage

give.summary(sample, probs=c(0.5, 0.025, 0.975))

Arguments

sample	a data frame or a vector with sampled values
probs	probabilities of the quantiles that are to be computed

Value

A matrix or a vector with the sample mean, quantiles and a Bayesian p-value.

Author(s)

Arnošt Komárek [e-mail]

Examples

## Example with a sample stored in a vector:
sample <- rnorm(1000)
give.summary(sample)

## Example with a sample stored in a data.frame:
sample <- data.frame(x=rnorm(1000), y=rgamma(1000, shape=1, rate=1))
give.summary(sample)

bayesSurv documentation built on Sept. 30, 2024, 9:34 a.m.