A Statistical Study of Some Nonparametric Estimators of the Logistic Regression Model

Abstract

The study provides an estimate of the nonparametric binary logistic regression model with the likelihood of chronic lymphocytic leukemia depending on the factors affecting the injury (patient sex, patient's age, white blood cells, hemoglobinemia, hematoglocytes, platelets) and lymphocytic leukemia is one of the most dangerous diseases for human life, it may result in many complications that may lead to exposure to other types of blood Irrigation of cancer, uncontrollable. The study aims to identify the most important statistical methods in analyzing cancer patient data and identifying the most important influences on it, which are categorical variables, and their importance lies in how to implement predictions after obtaining the best logistical model. Using the mixed method of core estimator and smoothed slide to estimate an optimal smoothing parameter using legitimate transit and generalized legitimate transit, it was concluded that the mixed method of core estimator and smoothed slide (LBS) is the best through the comparison criterion average squared error.