| cp.calc {HH} | R Documentation |
Rearranges and improves the legibility of the output from
the
stepwise
function in S-Plus.
The output can be used for the Cp plot.
cp.calc works only in S-Plus.
Use
regsubsets
in R. The example below works in
both languages.
cp.calc(sw, data, y.name) ## S3 method for class 'cp.object': print(x, ...) ## S3 method for class 'cp.object': x[..., drop = TRUE]
sw |
Output from the S-Plus
stepwise
function. |
data |
Dataset name from which "sw" was calculated. |
y.name |
Name of response variable for which "sw" was calculated. |
x |
Object of class "cp.object". |
... |
Additional arguments to "[" or "print". |
drop |
Argument to the print function. |
"cp.object", which is a data.frame containing information
about each model that was attempted with additional
attributes:
tss total sum of squares,
n number of observations,
y.name response variable,
full.i row name of full model. The columns are
p |
number of parameters in the model |
cp |
Cp statistic |
aic |
AIC statistic |
rss |
Residual sum of squares |
r2 |
R^2 |
r2.adj |
Adjusted R^2 |
xvars |
X variables |
sw.names |
Model name produced by stepwise. |
Richard M. Heiberger <rmh@temple.edu>
Heiberger, Richard~M. and Holland, Burt (2004). Statistical Analysis and Data Display: An Intermediate Course with Examples in S-Plus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0-387-40270-5.
## This example is from Section 9.15 of Heiberger and Holland (2004).
usair <- read.table(hh("datasets/usair.dat"),
col.names=c("SO2","temp","mfgfirms","popn",
"wind","precip","raindays"))
splom(~usair, main="U.S. Air Pollution Data with SO2 response", cex=.5)
## export.eps(hh("regb/figure/regb.f1.usair.eps"))
usair$lnSO2 <- log(usair$SO2)
usair$lnmfg <- log(usair$mfgfirms)
usair$lnpopn <- log(usair$popn)
usair[1:3,] ## lnSO2 is in position 8, SO2 is in position 1
## lnmfg is in position 9, lnpopn is in position 10
splom(~usair[, c(8,2,9,10,5:7)],
main="U.S. Air Pollution Data with 3 log-transformed variables",
cex=.5)
## export.eps(hh("regb/figure/regb.f2.usair.eps"))
if.R(s={
usair.step <- stepwise(y=usair$lnSO2,
x=usair[, c(2,9,10,5:7)],
method="exhaustive",
plot=FALSE, nbest=2)
## print for pedagogical purposes only. The plot of cp ~ p is more useful.
## The line with rss=1e35 is a stepwise() bug, that we reported to S-Plus.
print(usair.step, digits=4)
usair.cp <- cp.calc(usair.step, usair, "lnSO2")
## print for pedagogical purposes only. The plot of cp ~ p is more useful.
usair.cp
tmp <- (usair.cp$cp <= 10)
usair.cp[tmp,]
old.par <- par(mar=par()$mar+c(0,1,0,0))
tmp <- (usair.cp$cp <= 10)
plot(cp ~ p, data=usair.cp[tmp,], ylim=c(0,10), type="n", cex=1.3)
abline(b=1)
text(x=usair.cp$p[tmp], y=usair.cp$cp[tmp],
row.names(usair.cp)[tmp], cex=1.3)
title(main="Cp plot for usair.dat, Cp<10")
par(old.par)
## export.eps(hh("regb/figure/regb.f3.usair.eps"))
},r={
usair.regsubset <- regsubsets(lnSO2~lnmfg+lnpopn+precip+raindays+temp+wind, data=usair, nbest=2)
usair.subsets.Summary <- summary_HH(usair.regsubset)
tmp <- (usair.subsets.Summary$cp <= 10)
usair.subsets.Summary[tmp,]
plot(usair.subsets.Summary[tmp,], statistic='cp', legend=FALSE)
usair.lm7 <- lm.regsubsets(usair.regsubset, 7)
anova(usair.lm7)
summary(usair.lm7)
})
vif(lnSO2 ~ temp + lnmfg + lnpopn + wind + precip + raindays, data=usair)
vif(lnSO2 ~ temp + lnmfg + wind + precip, data=usair)
usair.lm <- lm(lnSO2 ~ temp + lnmfg + wind + precip, data=usair)
anova(usair.lm)
summary(usair.lm, corr=FALSE)