predict.bayescopulaglm: Predictive posterior sample from copula GLM

In bayescopulareg: Bayesian Copula Regression

Description

Sample from the predictive posterior density of a copula generalized linear model regression

Usage

## S3 method for class 'bayescopulaglm'
predict(object, newdata, nsims = 1, ...)

Arguments

object	Result from calling bayescopulaglm
newdata	data.frame of new data
nsims	number of posterior draws to take. The default and minimum is 1. The maximum is the number of simulations in object
...	further arguments passed to or from other methods

Value

array of dimension c(n, J, nsims) of predicted values, where J is the number of endpoints

Examples

set.seed(1234)
n <- 100
M <- 1000

x <- runif(n, 1, 2)
y1 <- 0.25 * x + rnorm(100)
y2 <- rpois(n, exp(0.25 * x))

formula.list <- list(y1 ~ 0 + x, y2 ~ 0 + x)
family.list <- list(gaussian(), poisson())
data = data.frame(y1, y2, x)

## Perform copula regression sampling with default
## (noninformative) priors
sample <- bayescopulaglm(
  formula.list, family.list, data, M = M
)
predict(sample, newdata = data)

bayescopulareg documentation built on Jan. 13, 2021, 8:04 a.m.