CI: Calculation of the posterior credible intervals for...

In yanbowisc/SIMP: Bayesian Simultaneous Partial Envelope Model

Calculation of the posterior credible intervals for regression parameters

Description

Calculation of the posterior credible intervals for regression parameters

Usage

CI(SIMP.fit, combined = T, Chain.no = 1, levels = 0.95)

Arguments

SIMP.fit	The MCMC output from SIMP() function.
combined	Logical. Indicate whether posterior samples (after burn-in) from all chains should be combined to calculate the posterior credible interval. If there is only one chain, then there is no difference by indicating this parameter to be TRUE or FALSE.
Chain.no	If combined = FALSE, we need to indicate which chain should be used for the calculation of posterior credible interval. Chain.no must be an integer between 1 and the number of chains.
levels	Significance level, default to be 0.95.

Examples

## Not run: 
library(SIMP)
library(Renvlp)
data(wheatprotein) # Load Renvlp package only for wheatprotein dataset.
set.seed(1)
X1C = wheatprotein[, 4:5]
X1D = as.matrix(wheatprotein[, 8], ncol = 1)
X2 = wheatprotein[, 6:7]
Y = wheatprotein[, 1:3]
MC_output <- SIMP(X1C = X1C, X1D = X1D, X2 = X2,
                  Y = Y, dx = 1, dy = 1, n.iter = 1e4)
CI(MC_output)

## End(Not run)

yanbowisc/SIMP documentation built on Oct. 30, 2022, 1:33 a.m.