## Using occupational prestige data
data(Prestige, package = "carData")
Prestige <- transform(Prestige, income = income / 1000)
## Fit a polywog model with bootstrap iterations
## (note: using low convergence threshold to shorten computation time of the
## example, *not* recommended in practice!)
set.seed(22)
fit1 <- polywog(prestige ~ education + income + type,
data = Prestige,
degree = 2,
boot = 5,
thresh = 1e-4)
## Basic information
print(fit1)
summary(fit1)
## See how fitted values change with education holding all else fixed
predVals(fit1, "education", n = 10)
## Plot univariate relationships
plot(fit1)
## Use SCAD instead of adaptive LASSO
fit2 <- update(fit1, method = "scad", thresh = 1e-3)
cbind(coef(fit1), coef(fit2))
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