Rearranges and improves the legibility of the output from
the
stepwise
function in SPlus.
The output can be used for the Cp plot.
cp.calc
works only in SPlus.
Use
regsubsets
in R. The example below works in
both languages.
1 2 3 4 5 6 7 
sw 
Output from the SPlus

data 
Dataset name from which 
y.name 
Name of response variable for which 
x 
Object of class 
... 
Additional arguments to 
drop 
Argument to the 
"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 
Richard M. Heiberger <rmh@temple.edu>
Heiberger, Richard M. and Holland, Burt (2004). Statistical Analysis and Data Display: An Intermediate Course with Examples in SPlus, R, and SAS. Springer Texts in Statistics. Springer. ISBN 0387402705.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62  ## This example is from Section 9.15 of Heiberger and Holland (2004).
data(usair)
if.R(s={usair < usair}, r={})
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 logtransformed variables",
cex=.5)
## export.eps(hh("regb/figure/regb.f2.usair.eps"))
if.R(s={
usair.step < stepwise(y=usair$lnSO2,
x=usair[, c(2,9,10,5:7)],
method="exhaustive",
plot=FALSE, nbest=2)
## print for pedagogical purposes only. The plot of cp ~ p is more useful.
## The line with rss=1e35 is a stepwise() bug, that we reported to SPlus.
print(usair.step, digits=4)
usair.cp < cp.calc(usair.step, usair, "lnSO2")
## print for pedagogical purposes only. The plot of cp ~ p is more useful.
usair.cp
tmp < (usair.cp$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 < leaps::regsubsets(lnSO2~lnmfg+lnpopn+precip+raindays+temp+wind,
data=usair, nbest=2)
usair.subsets.Summary < summaryHH(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)

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