Description Author(s) References See Also Examples
Model-diagnostics based on cumulative residuals
Klaus K. Holst <kkho@biostat.ku.dk>
D.Y. Lin and L.J. Wei and Z. Ying (2002) Model-Checking Techniques Based on Cumulative Residuals. Biometrics, Volume 58, pp 1-12.
John Q. Su and L.J. Wei (1991) A lack-of-fit test for the mean function in a generalized linear model. Journal. Amer. Statist. Assoc., Volume 86, Number 414, pp 420-426.
cox.aalen
in the
timereg
-package for similar GoF-methods for
survival-data.
1 |
Loading 'gof' version 0.9.1
cumres> sim1 <- function(n=100, f=function(x1,x2) {10+x1+x2^2}, sd=1, seed=1) {
cumres+ if (!is.null(seed))
cumres+ set.seed(seed)
cumres+ x1 <- rnorm(n);
cumres+ x2 <- rnorm(n)
cumres+ X <- cbind(1,x1,x2)
cumres+ y <- f(x1,x2) + rnorm(n,sd=sd)
cumres+ d <- data.frame(y,x1,x2)
cumres+ return(d)
cumres+ }
cumres> d <- sim1(100); l <- lm(y ~ x1 + x2,d)
cumres> system.time(g <- cumres(l, R=100, plots=50))
user system elapsed
0.086 0.003 0.100
cumres> g
Kolmogorov-Smirnov-test: p-value=0.32
Cramer von Mises-test: p-value=0.36
Based on 100 realizations. Cumulated residuals ordered by predicted-variable.
---
Kolmogorov-Smirnov-test: p-value=0.51
Cramer von Mises-test: p-value=0.26
Based on 100 realizations. Cumulated residuals ordered by x1-variable.
---
Kolmogorov-Smirnov-test: p-value=0
Cramer von Mises-test: p-value=0
Based on 100 realizations. Cumulated residuals ordered by x2-variable.
---
cumres> ## No test:
cumres> ##D plot(g)
cumres> ## End(No test)
cumres> g1 <- cumres(l, c("y"), R=100, plots=50)
cumres> g1
Kolmogorov-Smirnov-test: p-value=0.26
Cramer von Mises-test: p-value=0.32
Based on 100 realizations. Cumulated residuals ordered by predicted-variable.
---
cumres> g2 <- cumres(l, c("y"), R=100, plots=50, b=0.5)
cumres> g2
Kolmogorov-Smirnov-test: p-value=0.39
Cramer von Mises-test: p-value=0.21
Based on 100 realizations. Cumulated residuals ordered by predicted-variable.
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