# NOT RUN {
scatterplot(prestige ~ income, data=Prestige)
scatterplot(prestige ~ income, data=Prestige, smoother=gamLine)
scatterplot(prestige ~ income, data=Prestige, smoother=quantregLine)
scatterplot(prestige ~ income | type, data=Prestige)
scatterplot(prestige ~ income | type, data=Prestige, smoother=gamLine)
scatterplot(prestige ~ income | type, data=Prestige, smoother=quantregLine)
scatterplot(prestige ~ income | type, data=Prestige, smoother=NULL)
scatterplot(prestige ~ income | type, data=Prestige, spread=TRUE)
scatterplot(prestige ~ income | type, data=Prestige, smoother=gamLine, spread=TRUE)
scatterplot(prestige ~ income | type, data=Prestige, smoother=quantregLine, spread=TRUE)
scatterplot(weight ~ repwt | sex, spread=TRUE, data=Davis, smoother=loessLine)
scatterplot(weight ~ repwt | sex, spread=TRUE, data=Davis, smoother=gamLine) # messes up
scatterplot(weight ~ repwt | sex, spread=TRUE, data=Davis, smoother=quantregLine) # robust
set.seed(12345)
w <- 1 + rpois(100, 5)
x <- rnorm(100)
p <- 1/(1 + exp(-(x + 0.5*x^2)))
y <- rbinom(100, w, p)
scatterplot(y/w ~ x, smoother=gamLine,
smoother.args=list(family="binomial", weights=w))
scatterplot(y/w ~ x, smoother=gamLine,
smoother.args=list(family=binomial, link="probit", weights=w))
scatterplot(y/w ~ x, smoother=gamLine,
smoother.args=list(family=binomial, link="probit", weights=w))
scatterplot(y/w ~ x, smoother=loessLine, reg=FALSE)
y <- rbinom(100, 1, p)
scatterplot(y ~ x, smoother=gamLine, smoother.args=list(family=binomial))
# }
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