2017AIP conference proceedingsRequires access

Zero inflated negative binomial-Sushila distribution and its application

Darika Yamrubboon, Ampai Thongteeraparp, Winai Bodhisuwan, Katechan Jampachaisri

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Abstract

A new zero inflated distribution is proposed in this work, namely the zero inflated negative binomial-Sushila distribution. The new distribution which is a mixture of the Bernoulli and negative binomial-Sushila distributions is an alternative distribution for the excessive zero counts and over-dispersion. Some characteristics of the proposed distribution are derived including probability mass function, mean and variance. The parameter estimation of the zero inflated negative binomial-Sushila distribution is also implemented by maximum likelihood method. In application, the proposed distribution can provide a better fit than traditional distributions: zero inflated Poisson and zero inflated negative binomial distributions.

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What this paper is about

A new zero inflated distribution is proposed in this work, namely the zero inflated negative binomial-Sushila distribution. The new distribution which is a mixture of the Bernoulli and negative binomial-Sushila distributions is an alternative distribution for the excessive zero counts and over-dispersion. Some characteristics of the proposed distribution are derived including probability mass function, mean and variance. The parameter estimation of the zero inflated negative binomial-Sushila distribution is also implemented by maximum likelihood method. In application, the proposed distribution can provide a better fit than traditional distributions: zero inflated Poisson and zero inflated negative binomial distributions.

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Available abstract

A new zero inflated distribution is proposed in this work, namely the zero inflated negative binomial-Sushila distribution. The new distribution which is a mixture of the Bernoulli and negative binomial-Sushila distributions is an alternative distribution for the excessive zero counts and over-dispersion. Some characteristics of the proposed distribution are derived including probability mass function, mean and variance. The parameter estimation of the zero inflated negative binomial-Sushila distribution is also implemented by maximum likelihood method. In application, the proposed distribution can provide a better fit than traditional distributions: zero inflated Poisson and zero inflated negative binomial distributions.

Key concepts: Negative binomial distribution, Beta-binomial distribution, Poisson binomial distribution, Binomial distribution, Beta negative binomial distribution, Compound Poisson distribution, Zero (linguistics), Zero-inflated model

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