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## tests of the simulate.lm method, added Feb 2009
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## tests of the simulate.lm method, added Feb 2009
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options(digits = 5)
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options(digits = 5)
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## cases should be named
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## cases should be named
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load("hills.rda") # copied from package MASS
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hills <- readRDS("hills.rds") # copied from package MASS
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fit1 <- lm(time ~ dist, data = hills)
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fit1 <- lm(time ~ dist, data = hills)
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set.seed(1)
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set.seed(1)
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simulate(fit1, nsim = 3)
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simulate(fit1, nsim = 3)
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## and weights should be taken into account
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## and weights should be taken into account
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fit2 <- lm(time ~ -1 + dist + climb, hills[-18, ], weight = 1/dist^2)
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fit2 <- lm(time ~ -1 + dist + climb, hills[-18, ], weight = 1/dist^2)
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coef(summary(fit2))
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coef(summary(fit2))
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set.seed(1)
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( ys <- simulate(fit2, nsim = 3) )
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set.seed(1); ( ys <- simulate(fit2, nsim = 3) )
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for(i in seq_len(3))
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for(i in seq_len(3))
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    print(coef(summary(update(fit2, ys[, i] ~ .))))
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    print(coef(summary(update(fit2, ys[, i] ~ .))))
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## should be identical to glm(*, gaussian):
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fit2. <- glm(time ~ -1 + dist + climb, family=gaussian, data=hills[-18, ],
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             weight = 1/dist^2)
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set.seed(1); ys. <- simulate(fit2., nsim = 3)
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stopifnot(all.equal(ys, ys.))
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## Poisson fit
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## Poisson fit
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load("anorexia.rda") # copied from package MASS
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load("anorexia.rda") # copied from package MASS
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fit3 <- glm(Postwt ~ Prewt + Treat + offset(Prewt),
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fit3 <- glm(Postwt ~ Prewt + Treat + offset(Prewt),
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            family = gaussian, data = anorexia)
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            family = gaussian, data = anorexia)