Mixture-Link-Poisson-Distribution: Distribution functions

Description Usage Arguments Value References Examples

Description

Functions for Mixture Link Poisson distribution

Usage

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r.mixlink.pois(n, mean, Pi, kappa, save.latent = FALSE)

d.mixlink.pois(y, mean, Pi, kappa, log = FALSE)

p.mixlink.pois(y, mean, Pi, kappa)

Arguments

n

Number of observations to draw

mean

Parameter \vartheta of distribution

Pi

Parameter \bm{π} of distribution

kappa

Parameter κ of distribution

save.latent

Save intermediate latent variables used during draw.

y

Argument of pdf or cdf

log

Return log of the result (TRUE or FALSE)

Value

d.mixlink.pois gives the density, p.mixlink.pois gives the distribution function, and r.mixlink.pois generates random deviates.

References

Andrew M. Raim, Nagaraj K. Neerchal, and Jorge G. Morel. An Extension of Generalized Linear Models to Finite Mixture Outcomes. arXiv preprint: 1612.03302

Examples

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  mean.true <- 20
  Pi.true <- c(1/4, 3/4)
  kappa.true <- 0.5
  r.mixlink.pois(n = 30, mean.true, Pi.true, kappa.true)
  d.mixlink.pois(y = 21, mean.true, Pi.true, kappa.true)
  d.mixlink.pois(y = 21, mean.true, Pi.true, kappa.true, log = TRUE)
  p.mixlink.pois(y = 21, mean.true, Pi.true, kappa.true)

mixlink documentation built on May 2, 2019, 5:11 a.m.