Description Usage Arguments Value References Examples
Functions for Mixture Link Poisson distribution
1 2 3 4 5 | 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)
|
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) |
d.mixlink.pois
gives the density,
p.mixlink.pois
gives the distribution function, and
r.mixlink.pois
generates random deviates.
Andrew M. Raim, Nagaraj K. Neerchal, and Jorge G. Morel. An Extension of Generalized Linear Models to Finite Mixture Outcomes. arXiv preprint: 1612.03302
1 2 3 4 5 6 7 | 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)
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