sigma.hat {arm} | R Documentation |
This generic function extracts residual errors from a fitted model.
sigma.hat(object,...) ## S4 method for signature 'lm': sigma.hat(object) ## S4 method for signature 'glm': sigma.hat(object) ## S4 method for signature 'mer': sigma.hat(object)
object |
any fitted model object of lm , glm and mer class |
... |
other arguments |
Andrew Gelman gelman@stat.columbia.edu; Yu-Sung Su ys463@columbia.edu
display
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summary
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lm
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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)