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Create pairs of correlated random numbers.
RndPairs(n, r, rdist1 = rnorm(n = n, mean = 0, sd = 1),
rdist2 = rnorm(n = n, mean = 0, sd = 1))RndWord(size, length, x = LETTERS, replace = TRUE, prob = NULL)
number of pairs. If length(n) > 1, the length is taken to be the number required.
the correlation between the two sets.
the distribution of the random vector X1 and X2. Default is standard normal distribution.
a non-negative integer giving the number of artificial words to build.
a non-negative integer giving the length of the words.
elements to choose from.
Should sampling be with replacement?
a vector of probability weights for obtaining the elements of the vector being sampled.
a data.frame with 2 columns, X1 and X2 containing the random numbers
# NOT RUN {
# produce 100 pairs of a normal distributed random number with a correlation of 0.7
d.frm <- RndPairs(n=100, r=0.7)
plot(d.frm)
lines(lm(X2 ~ X1,d.frm))
# change the distribution
d.frm <- RndPairs(n=100, r=0.7, rdist2 = rlnorm(n = 100, meanlog = 1, sdlog = .8))
d.frm <- RndPairs(n=100, r=0.7, rdist2 = runif(n = 100, -1, 4))
x <- StrCap(sapply(sample(3:15, 10), function(i) RndWord(1, i, x=letters)))
# produce some artificial words with defined probabilities for the letters
p <- c(6.51,1.89,3.06,5.08,17.4,1.66,3.01,4.76,7.55,0.27,1.21,3.44,2.53,
9.78,2.51,0.79,0.02,7,7.27,6.15,4.35,0.67,1.89,0.03,0.04,1.13)
sapply(sample(3:15, 10), function(i) RndWord(1, i, x=letters, prob=p))
# }
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