ztplnmMLE {ztpln}

MLE for the Zero-truncated Poisson Lognormal mixture distribtuion

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)