simult.pvalue: Compute a simultaneous p-value from a sample for a vector...

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

Compute a simultaneous p-value from a sample for a vector valued parameter.

Description

The p-value is computed as 1 - the credible level of the credible region which just cover the point (0, 0, ..., 0)'.

The function returns also the simultaneous credible region (rectangle) with a specified credible level.

Usage

simult.pvalue(sample, precision=0.001, prob=0.95)
## S3 method for class 'simult.pvalue'
print(x, ...)

Arguments

sample	a data frame or matrix with sampled values (one column = one parameter)
precision	precision with which the p-value is to be computed
prob	probability for which the credible region is to be computed
x	an object of class simult.pvalue
...	who knows

Value

An object of class 'simult.pvalue'.

Author(s)

Arnošt Komárek [e-mail]

References

Besag, J., Green, P., Higdon, D. and Mengersen, K. (1995). Bayesian computation and stochastic systems (with Discussion). Statistical Science, 10, 3 - 66. page 30

Held, L. (2004). Simultaneous posterior probability statements from Monte Carlo output. Journal of Computational and Graphical Statistics, 13, 20 - 35.

Examples

m <- 1000
sample <- data.frame(x1=rnorm(m), x2=rnorm(m), x3=rnorm(m))
simult.pvalue(sample)

sample <- data.frame(x1=rnorm(m), x2=rnorm(m), x3=rnorm(m, mean=2))
simult.pvalue(sample)

sample <- data.frame(x1=rnorm(m), x2=rnorm(m), x3=rnorm(m, mean=5))
simult.pvalue(sample, prob=0.99, precision=0.0001)

bayesSurv documentation built on Dec. 5, 2022, 5:22 p.m.