zictp.fit: Maximum Likelihood Estimation for the Zero-Modified CTP...

In zmctp: Zero-Modified Complex 'Tri-Parametric' Pearson Distribution for Overdispersed Count Data

Maximum Likelihood Estimation for the Zero-Modified CTP Distribution

Description

Fits the Zero-Modified Complex TriParametric Pearson (ZM-CTP) distribution to count data using maximum likelihood estimation.

A logit reparameterization is used for omega to ensure 0 < omega < 1, and a log reparameterization is used for gamma so that gama = 2*a + 2 + exp(eta), which guarantees variance existence throughout optimization.

Usage

zictp.fit(
  x,
  a_start = NULL,
  b_start = NULL,
  gama_start = NULL,
  omega_start = NULL,
  method = "BFGS"
)

Arguments

x	Numeric vector of nonnegative counts.
a_start	Optional starting value for parameter a.
b_start	Optional starting value for parameter b.
gama_start	Optional starting value for parameter gamma.
omega_start	Optional starting value for omega (0 < omega < 1).
method	Optimization method (default: "BFGS").

Value

An object of class '"zictpfit"'.

Examples

set.seed(123)
x <- rzictp(30, a = 1, b = 0.5, gama = 5, omega = 0.3)
fit <- zictp.fit(x)
fit$estimates

zmctp documentation built on Sept. 20, 2026, 5:07 p.m.