Add to ORKGRobust and efficient estimation of the parameters of the negative binomial distribution. Two-step estimation procedure, with computation of an initial estimate which is used to identify and downweight outliers. Then a weighted maximum likelihood estimate is computed. The initial estimator is a minimum disparity estimator
Background. The negative binomial distribution is used commonly throughout biology as a model for ov...
The negative binomial distribution is used commonly throughout biology as a model for overdispersed ...
BackgroundThe negative binomial distribution is used commonly throughout biology as a model for over...
Robust and efficient estimation of the parameters of the negative binomial distribution. Two-step e...
In this article we investigate a class of moment-based estimators, called power method estimators, w...
In this article we investigate a class of moment-based estimators, called power method estimators, w...
In this article we investigate a class of moment-based estimators, called power method estimators, w...
Negative binomial regression is commonly employed to analyze overdispersed count data. With small to...
We consider robust parametric procedures for univariate discrete distributions, focusing on the nega...
A size-biased negative binomial distribution, a particular case of the weighted negative binomial di...
A maximum weighted likelihood method is proposed to combine all the relevant data from different so...
Negative binomial regression is commonly employed to analyze overdispersed count data. With small t...
Negative binomial distribution, Maximum likelihood, Method of moments, Efficiency of estimators, INA...
The negative binomial distribution was perhaps the first probability distribution, considered in sta...
A popular way to model overdispersed count data, such as the number of falls reported during interve...
Background. The negative binomial distribution is used commonly throughout biology as a model for ov...
The negative binomial distribution is used commonly throughout biology as a model for overdispersed ...
BackgroundThe negative binomial distribution is used commonly throughout biology as a model for over...
Robust and efficient estimation of the parameters of the negative binomial distribution. Two-step e...
In this article we investigate a class of moment-based estimators, called power method estimators, w...
In this article we investigate a class of moment-based estimators, called power method estimators, w...
In this article we investigate a class of moment-based estimators, called power method estimators, w...
Negative binomial regression is commonly employed to analyze overdispersed count data. With small to...
We consider robust parametric procedures for univariate discrete distributions, focusing on the nega...
A size-biased negative binomial distribution, a particular case of the weighted negative binomial di...
A maximum weighted likelihood method is proposed to combine all the relevant data from different so...
Negative binomial regression is commonly employed to analyze overdispersed count data. With small t...
Negative binomial distribution, Maximum likelihood, Method of moments, Efficiency of estimators, INA...
The negative binomial distribution was perhaps the first probability distribution, considered in sta...
A popular way to model overdispersed count data, such as the number of falls reported during interve...
Background. The negative binomial distribution is used commonly throughout biology as a model for ov...
The negative binomial distribution is used commonly throughout biology as a model for overdispersed ...
BackgroundThe negative binomial distribution is used commonly throughout biology as a model for over...