DHNBINOM: Double-Hurdle Model for Negative Binomial Distribution

In ebalderama/ZimulatE: Simulates Zero-Inflated, Hurdle, and Double-Hurdle Models

Description

Density, distribution function, quantile function and random generation for the hurdle model using negative binomial distribution with parameters theta, size, and prob.

Usage

ddhnbinom(
  x,
  theta = 0.5,
  theta_1 = 0.1,
  size = 0.9,
  mu = 0.9,
  scale = 1,
  shape = 1,
  threshold = 3,
  log = FALSE
)

pdhnbinom(
  q,
  theta = 0.5,
  theta_1 = 0.1,
  size = 0.9,
  mu = 0.9,
  scale = 1,
  shape = 1,
  lower.tail = TRUE,
  log.p = FALSE,
  threshold
)

rdhnbinom(
  n,
  theta = 0.5,
  theta_1 = 0.1,
  size = 0.9,
  mu = 0.9,
  scale = 1,
  shape = 1,
  threshold = 3
)

Arguments

x, q	vector of quantiles
theta	zero generating parameter (probability of zeros)
theta_1	probability of a count at or above mu, conditional on non-zero count
size	number of successes (dispersion parameter)
mu	probability of success in each trial. 0 < prob < 1
scale	scale parameter
shape	shape parameter
threshold	second hurdle
log, log.p	logical; if TRUE, probabilities p are given as log(p).
lower.tail	logical; if TRUE (default), probabilities are P[X %leq x], otherwise, P[X > x].
n	number of observations
p	vector of probabilities

Value

dhnbinom gives the density, phnbinom gives the distribution function, qhnbinom gives the quantile function, and rhnbinom generates random deviates.

ebalderama/ZimulatE documentation built on Dec. 20, 2021, 3:12 a.m.