Results 81 to 90 of about 134 (94)
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Jackknife Kibria-Lukman estimator for the beta regression model

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

Performance of some robust improved Kibria-Lukman M-estimators for linear regression model in presence of multicollinearity and outliers

Communications in Statistics Part B: Simulation and Computation
B M Golam Kibria   +2 more
exaly   +2 more sources

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

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  

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

Concurrency Computation Practice and Experience, 2023
, Aslam Muhammad
exaly  

Kibria‐Lukmantype estimator for gamma regression model

Concurrency Computation Practice and Experience, 2023
Gladys Shewa
exaly  

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

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

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