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Selection of A New Biasing Parameter for the Jackknife Kibria-Lukman Estimator for the Negative Binomial Regression Model

NIPES Journal of Science and Technology Research
The negative binomial regression model (NBRM) is a generalized linear model that relaxes the restrictive assumption of the Poisson regression model when the variance is equal to the mean. The estimation of the parameters of the NBRM is obtained using the maximum likelihood (ML) method.
Henrietta Ebele Oranye   +9 more
openaire   +1 more source

Jackknife Kibria-Lukman estimator for the beta regression model

Communications in Statistics - Theory and Methods, 2023
Tuba Koç, Emre Dünder
openaire   +1 more source

Kibria–Lukman estimator for the zero inflated negative binomial regression model: theory, simulation and applications

Communications in Statistics - Simulation and Computation, 2023
Muhammad Nauman Akram   +3 more
openaire   +1 more source

Modified jackknife Kibria–Lukman estimator for the Poisson regression model

Concurrency Computation Practice and Experience, 2022
Ugwuowo Fidelis Ifeanyi   +1 more
exaly  

Comparisons Among the Preliminary Test Kibria-Lukman Estimator Based on Three Large Sample Tests in the Linear Regression Model

Proceedings of the 2023 6th International Conference on Machine Learning and Natural Language Processing, 2023
Xiangyun Deng, Jibo Wu
openaire   +1 more source

A robust Kibria–Lukman estimator for linear regression model to combat multicollinearity and outliers

Concurrency Computation Practice and Experience, 2023
Aslam Muhammad
exaly  

Kibria-Lukman type estimator for gamma regression model

Concurrency Computation Practice and Experience, 2023
Gladys Shewa
exaly  

Influence diagnostics in the linear model with Kibria–Lukman estimator

Communications in Statistics - Simulation and Computation
T. J. Adejumo   +3 more
openaire   +1 more source

On the jackknife Kibria-Lukman estimator for the linear regression model

Communications in Statistics Part B: Simulation and Computation, 2023
Kingsley Chinedu Arum   +2 more
exaly  

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