Likelihood-based methods for the zero-one-two inflated Poisson model with applications to biomedicine
DOI10.1080/00949655.2021.1970162zbMath1530.62017OpenAlexW3196880117MaRDI QIDQ6050545
Man-Lai Tang, Yu-An Sun, Shishun Zhao, Guo-Liang Tian, Unnamed Author
Publication date: 19 September 2023
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2021.1970162
EM algorithmbootstrap confidence intervalsFisher scoring algorithmzero-and-one-inflated Poisson modelzero-one-two-inflated Poisson distribution
Parametric tolerance and confidence regions (62F25) Applications of statistics to biology and medical sciences; meta analysis (62P10) Point estimation (62F10)
Cites Work
- Unnamed Item
- Analysis of zero-adjusted count data
- Estimating the dimension of a model
- Properties of the zero-and-one inflated Poisson distribution and likelihood-based inference methods
- The Calculation of Posterior Distributions by Data Augmentation
- Zero-Inflated Poisson Regression, with an Application to Defects in Manufacturing
- Statistical inference for zero-and-one-inflated poisson models
- Tools for statistical inference. Methods for the exploration of posterior distributions and likelihood functions.
- A new look at the statistical model identification
This page was built for publication: Likelihood-based methods for the zero-one-two inflated Poisson model with applications to biomedicine
