Convert normal to negative binomial

See the help for `qnbinom()` for further info about prob versus mu parameter specification. Thanks for the suggested code, David Hugh-Jones!

Usage

norm2nbinom(
  x,
  size,
  prob,
  mu,
  lower.tail = TRUE,
  log.p = FALSE,
  x_mu = mean(x),
  x_sd = stats::sd(x)
)

Arguments

x: the normally distributed vector
size: target for number of successful trials, or dispersion parameter (the shape parameter of the gamma mixing distribution). (size > 0)
prob: the probability of success on each trial (0 to 1)
mu: alternative parametrization via mean (only specify one of prob or mu)
lower.tail: logical; if TRUE (default), probabilities are P[X x], otherwise, P[X > x]
log.p: logical; if TRUE, probabilities p are given as log(p)
x_mu: the mean of x (calculated from x if not given)
x_sd: the SD of x (calculated from x if not given)

Value

a vector with a negative binomial distribution

Examples


x <- rnorm(10000)
y <- norm2nbinom(x, 1, prob = 0.5)
z <- norm2nbinom(x, 1, mu = 1)
g <- ggplot2::ggplot() + ggplot2::geom_point(ggplot2::aes(x, y))
ggExtra::ggMarginal(g, type = "histogram")