random.functions {kyotil} | R Documentation |
rbern generates Bernoulli random variables.
dbern(x, prob, log = FALSE) dcorbern(x, p, a, log = FALSE) dmixnorm(x, mix.p, sd1, sd2, log = FALSE) dnorm.norm.gamma(x, p, same.distr = FALSE, log = FALSE) rbern(n, prob, generalized = FALSE) rbigamma(n, shape.1, shape.2, rate.1, rate.2, rho) rbilogistic(n, loc.1, loc.2, scale.1, scale.2, rho) rejective.sampling(N, n, pik) rnorm.cor(n, mu, sd, alpha) rnorm.norm.gamma(n, mu.0, lambda, alpha, beta) rmixnorm (n, mix.p, mu1, mu2, sd1, sd2) rdoublexp(n, location=0, scale=1) ddoublexp(x, location=0, scale=1) qdoublexp(p, location=0, scale=1) pdoublexp(q, location=0, scale=1) rbidoublexp(n, loc.1, loc.2, scale.1, scale.2, rho)
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location |
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scale |
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x |
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prob |
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log |
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p |
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a |
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mix.p |
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sd1 |
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sd2 |
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same.distr |
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n |
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generalized |
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N |
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pik |
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mu |
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mu1 |
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mu2 |
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sd |
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alpha |
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mu.0 |
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lambda |
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beta |
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loc.1 |
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loc.2 |
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scale.1 |
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scale.2 |
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rate.1 |
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rate.2 |
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shape.1 |
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shape.2 |
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rho |
rbilogistic generates a bivariate logistic distribution for correlation coefficient 0.5, or [-0.271, 0.478].
In the former case it is generated by calling rbilogis
, part of the VGAM package; in the latter case it is generated via the AMH copular.
set.seed(1) rbern(n=10, p=1/2) rbern(n=2, p=c(.999,.001))