arm (version 1.9-1)

sigma.hat: Extract Residual Errors

Description

This generic function extracts residual errors from a fitted model.

Usage

sigma.hat(object,...)
"sigma.hat"(object,...)
"sigma.hat"(object,...)
"sigma.hat"(object,...)
"sigma.hat"(object,...)
"sigma.hat"(object,...)

Arguments

object

any fitted model object of lm, glm and merMod class

...

other arguments

See Also

display, summary, lm, glm, lmer

Examples

   group <- rep(1:10, rep(10,10))
   mu.a <- 0
   sigma.a <- 2
   mu.b <- 3
   sigma.b <- 4
   rho <- 0
   Sigma.ab <- array (c(sigma.a^2, rho*sigma.a*sigma.b,
                    rho*sigma.a*sigma.b, sigma.b^2), c(2,2))
   sigma.y <- 1
   ab <- mvrnorm (10, c(mu.a,mu.b), Sigma.ab)
   a <- ab[,1]
   b <- ab[,2]

   x <- rnorm (100)
   y1 <- rnorm (100, a[group] + b[group]*x, sigma.y)
   y2 <- rbinom(100, 1, prob=invlogit(a[group] + b*x))

   M1 <- lm (y1 ~ x)
   sigma.hat(M1)

   M2 <- bayesglm (y1 ~ x, prior.scale=Inf, prior.df=Inf)
   sigma.hat(M2) # should be same to sigma.hat(M1)

   M3 <- glm (y2 ~ x, family=binomial(link="logit"))
   sigma.hat(M3)

   M4 <- lmer (y1 ~ (1+x|group))
   sigma.hat(M4)

   M5 <- glmer (y2 ~ (1+x|group), family=binomial(link="logit"))
   sigma.hat(M5)