envel.res {Kmisc} | R Documentation |
~~ A concise (1-5 lines) description of what the function does. ~~
envel.res(obj, NMC = 199)
obj |
~~Describe obj here~~ |
NMC |
~~Describe NMC here~~ |
~~ If necessary, more details than the description above ~~
~Describe the value returned If it is a LIST, use
comp1 |
Description of 'comp1' |
comp2 |
Description of 'comp2' |
...
....
~~further notes~~
~Make other sections like Warning with section{Warning }{....} ~
~~who you are~~
~put references to the literature/web site here ~
~~objects to See Also as help
, ~~~
##---- Should be DIRECTLY executable !! ---- ##-- ==> Define data, use random, ##-- or do help(data=index) for the standard data sets. ## The function is currently defined as function(obj, NMC=199) { fit <- fitted(obj) X <- model.matrix(obj) td <- my.res(obj) n <- nrow(X) res <- matrix(0, NMC, n) for (i in 1:NMC) { if (all(class(obj)=="lm")) { y <- rnorm(n, fit) res[i, ] <- sort(my.res(glm(y~X, family=gaussian))) } else { if (obj$family$family=="binomial") { y <- rbinom(n, 1, fit) } if (obj$family$family=="poisson") { y <- rpois(n, fit) } res[i, ] <- sort(my.res(glm(y~X, family=obj$family))) } } faixa <- range(res) par.ori <- par(no.readonly = TRUE) par(mfrow=c(1,1), mar=c(3,3,3,1), mgp=c(1.7,0.7,0), las=1) qqnorm(td, xlab="Percentis da N(0,1)", ylab="Componente do Desvio", ylim=faixa, pch=16) par(new=T) qqnorm(apply(res, 2, quantile, 0.05), axes=FALSE, xlab="", ylab="", type="l", ylim=faixa, lty=1) par(new=T) qqnorm(apply(res, 2, quantile, 0.95), axes=FALSE, xlab="", ylab="", type="l", ylim=faixa, lty=1) par(par.ori) colnames(res) <- paste("a", 1:n, sep="") rownames(res) <- paste("s", 1:NMC, sep="") return(res) }