norm2nbinom: Convert normal to negative binomial

In faux: Simulation for Factorial Designs

Convert normal to negative binomial

Description

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")

faux documentation built on April 3, 2025, 7:44 p.m.