Random and Fixed Effects Selection for Weighted Ridge

Using penalized profiled log-likelihood and limited log-likelihood, respectively, together with the weighted ridge term, we offer a method in this study for choosing fixed random effects linear mixed models. Then, use restricted to perform depending on chosen tuning parameter. Second, choose effect parameters. There is no closed-form solution choice of effects, hence Newton-Raphson technique employed iteratively estimate We simulation show how well suggested strategy works. Lastly, two separate datasets methods further evaluate newly proposed model.