On some beta ridge regression estimators: method, simulation and application

DOI10.1080/00949655.2020.1867549OpenAlexW3124631997MaRDI QIDQ5065297

Kristofer Månsson, Muhammad Qasim, B. M. Golam Kibria

Publication date: 18 March 2022

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2020.1867549

zbMATH Keywords

mean squared errorsimulation studymulticollinearitybeta regression modelmedian squared error

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Generalized linear models (logistic models) (62J12) Statistics (62-XX)

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A new class of efficient and debiased two-step shrinkage estimators: method and application ⋮ A restricted gamma ridge regression estimator combining the gamma ridge regression and the restricted maximum likelihood methods of estimation ⋮ Generalized two-parameter estimators in the multinomial logit regression model: methods, simulation and application ⋮ A new biased estimator for the gamma regression model: Some applications in medical sciences ⋮ Inverse Gaussian Liu-type estimator ⋮ Improved shrinkage estimators in the beta regression model with application in econometric and educational data ⋮ On the Liu estimation of Bell regression model in the presence of multicollinearity

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