Zero-Modified Poisson-Lindley distribution with applications in zero-inflated and zero-deflated count data

12/12/2017
by   Danillo Xavier, et al.
0

The main object of this article is to present an extension of the zero-inflated Poisson-Lindley distribution, called of zero-modified Poisson-Lindley. The additional parameter π of the zero-modified Poisson-Lindley has a natural interpretation in terms of either zero-deflated/inflated proportion. Inference is dealt with by using the likelihood approach. In particular the maximum likelihood estimators of the distribution's parameter are compared in small and large samples. We also consider an alternative bias-correction mechanism based on Efron's bootstrap resampling. The model is applied to real data sets and found to perform better than other competing models.

READ FULL TEXT
research
01/29/2018

Reparametrization of COM-Poisson Regression Models with Applications in the Analysis of Experimental Data

In the analysis of count data often the equidispersion assumption is not...
research
10/25/2021

Poisson-modification of the Quasi Lindley distribution and its zero modification for over-dispersed count data

In this paper, an alternative mixed Poisson distribution is proposed by ...
research
10/30/2019

Software defect prediction with zero-inflated Poisson models

In this work we apply several Poisson and zero-inflated models for softw...
research
12/27/2021

Modeling Sparse Data Using MLE with Applications to Microbiome Data

Modeling sparse data such as microbiome and transcriptomics (RNA-seq) da...
research
07/08/2020

Modelling excess zeros in count data: A new perspective on modelling approaches

We consider models underlying regression analysis of count data in which...
research
08/15/2023

Robust Bayesian Tensor Factorization with Zero-Inflated Poisson Model and Consensus Aggregation

Tensor factorizations (TF) are powerful tools for the efficient represen...
research
02/17/2021

Unbiased Estimations based on Binary Classifiers: A Maximum Likelihood Approach

Binary classifiers trained on a certain proportion of positive items int...

Please sign up or login with your details

Forgot password? Click here to reset