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# Example of penalty from help page using lrm:
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n <- 1000 # define sample size
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set.seed(17) # so can reproduce the results
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age <- rnorm(n, 50, 10)
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blood.pressure <- rnorm(n, 120, 15)
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cholesterol <- rnorm(n, 200, 25)
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sex <- factor(sample(c('female','male'), n,TRUE))
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# Specify population model for log odds that Y=1
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L <- .4*(sex=='male') + .045*(age-50) +
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(log(cholesterol - 10)-5.2)*(-2*(sex=='female') + 2*(sex=='male'))
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# Simulate binary y to have Prob(y=1) = 1/[1+exp(-L)]
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y <- ifelse(runif(n) < plogis(L), 1, 0)
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f <- lrm(y ~ blood.pressure + sex * (age + rcs(cholesterol,4)),
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p <- pentrace(f, seq(.2,1,by=.05))
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p$diag # may learn something about fractional effective d.f.
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# for each original parameter
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# Example modified for ols:
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fols <- ols(blood.pressure ~sex * (age + rcs(cholesterol,4)), x=TRUE, y=TRUE)
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pols <- pentrace(fols, seq(0,10,by=.5))
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update(fols,penalty=10)
added
removed
tests/lrm.ols.penalty.r
