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simulated.census <- function (N=502202, p.male=0.55, seed.rng=42) {
# default N = population of Luxembourg, as estimate on 1 Jan 2010 (from http://en.wikipedia.org/wiki/Luxembourg)
# save current RNG state and set new seed (for reproducible data set)
runif(1) # make sure there is a .Random.seed
save.seed <- .Random.seed
set.seed(seed.rng, kind="default")
height2weight <- function (h, h0=170, w0=65, slope=1, curvature=0.01, sd.log=.2) {
x <- h - h0
w <- w0 + (slope * (1 + curvature * x)) * x
scale <- 2 ^ rnorm(length(w), 0, sd.log)
w * scale
}
height2shoe <- function (h, h0=170, s0=42, slope=0.2, sd=1) {
x <- h - h0
sizes <- s0 + slope * x + rnorm(length(s0), 0, sd)
round(2 * sizes) / 2
}
N.male <- round(N * p.male)
h.male <- rnorm(N.male, 180, 10)
w.male <- height2weight(h.male, h0=180, w0=75)
s.male <- height2shoe(h.male, h0=180, s0=44.5)
N.female <- N - N.male
h.female <- rnorm(N.female, 160, 10)
w.female <- height2weight(h.female, h0=160, w0=50, slope=0.5, curvature=0.02, sd.log=.15)
s.female <- height2shoe(h.female, h0=160, s0=38, slope=0.15)
males <- data.frame(height=h.male, weight=w.male, shoe.size=s.male, sex="m")
females <- data.frame(height=h.female, weight=w.female, shoe.size=s.female, sex="f")
FakeCensus <- rbind(males, females)
FakeCensus <- FakeCensus[sample(1:N), ]
rownames(FakeCensus) <- 1:N
# restore RNG state, then return generated data set
.Random.seed <<- save.seed
FakeCensus
}
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