ztplnmMLE: MLE for the Zero-truncated Poisson Lognormal mixture...

In mattocci27/ztpln: Zero-Truncated Poisson Lognormal Distribution

Description

ztplnmMLE fits the Zero-truncated Poisson lognormal mixture distribution to data and estimates parameters mean mu, standard deviation sig and mixture weight theta in the lognormal distribution.

Usage

ztplnmMLE(
  n,
  K = 2,
  lower_mu = rep(0, K),
  upper_mu = rep(log(max(n)), K),
  lower_sig = rep(0.001, K),
  upper_sig = rep(10, K),
  lower_theta = rep(0.001, K),
  upper_theta = rep(0.999, K),
  type1 = TRUE,
  message = FALSE
)

Arguments

n	a vector of counts
K	number of components
lower_mu, upper_mu	numeric values of lower and upper bounds for mean of the variables's natural logarithm.
lower_sig, upper_sig	numeric values of lower and upper bounds for standard deviation of the variables's natural logarithm
lower_theta, upper_theta	numeric values of lower and upper bounds for mixture weights.
type1	logical; if TRUE, Use type 1 ztpln else use type 2.
message	mean of lognormal distribution in sample 3.

Details

The function searches the maximum likelihood estimators of mean vector mu, standard deviation vector sig and mixture weight vector theta using the optimization procedures in nlminb.

Value

convergence	An integer code. 0 indicates successful convergence.
iterations	Number of iterations performed.
message	A character string giving any additional information returned by the optimizer, or NULL. For details, see PORT documentation.
evaluation	Number of objective function and gradient function evaluations
mu	Maximum likelihood estimates of mu
sig	Maximum likelihood estimates of sig
theta	Maximum likelihood estimates of theta
loglik	loglikelihood

Examples

y <- rztplnm(100, c(1, 10), c(2, 1), c(0.2, 0.8))
ztplnmMLE(y)

mattocci27/ztpln documentation built on Oct. 14, 2021, 12:52 a.m.