Stepwise regression includes regression models in which the predictive variables are selected by an automated algorithm. The stepwise method involves two approaches, namely, backward elimination and forward selection. Currently, SAS has several regression procedures capable of performing stepwise regression. Among them are REG, LOGISTIC, GLMSELECT and PHREG. PROC REG handles linear regression m...

Multiple Objective Programming (MOP) problems have become famous among many researchers due to more practical and realistic implementations. There have been a lot of methods proposed especially during the past four decades. In this paper, we develop a new algorithm based on a new approach to solve MOP problems by starting from a utopian point (which is usually infeasible) and moving towards the...

the moe and mor are controlled by production variables of particleboard process. now, the basic question is which of the particleboard variables is effective on bending strength property? 13 variables of internal scientific resources were measured with 100 repeats. the study steps include the following; liner regression or stepwise, genetic algorithm, and artificial neural network. the number o...

The existence of multiple likelihood maxima necessitates algorithms that explore a large part of the tree space. However, because of computational constraints, stepwise addition-based tree-searching methods do not allow for this exploration in reasonable time. Here, I present an algorithm that increases the speed at which the likelihood landscape can be explored. The iterative algorithm combine...

in this research,qsar study has been carried out on quinolizidinyl derivatives as potent inhibitors of acetyl and butyrylcholin esterase in alzheimer’s disease. despite significant research efforts in both industry and academia, there are currently no diseases modifying therapies available to treat this illness. significant evidence suggests that the pathology of ad is linked to generation of β...

A stepwise algorithm where the user starts with a preliminary model and adds new, nonlinear, parts to it is used to identify a nonlinear model of a rotational system. The user is assumed to roughly know where in the system there are nonlinearities and adds small black-box parts to the initial model to capture the nonlinearities. The stepwise algorithm gives well motivated parameter initializati...