Performance of a New Restricted Biased Estimator in Logistic Regression

A New Biased Estimator Derived from Principal Component Regression Estimator

A NEW APPROACH FOR PARAMETER ESTIMATION IN FUZZY LOGISTIC REGRESSION

Logistic regression analysis is used to model categorical dependent variable. It is usually used in social sciences and clinical research. Human thoughts and disease diagnosis in clinical research contain vagueness. This situation leads researchers to combine fuzzy set and statistical theories. Fuzzy logistic regression analysis is one of the outcomes of this combination and it is used in situa...

Maximum Weighted Likelihood Estimator in Logistic Regression

The least weighted squares estimator is a well known technique in robust regression. Its likelihood analogy in logistic regression is the maximum weighted likelihood estimator, proposed in Vandev and Neykov (1998) and Mueller and Neykov (2003). This article mentions already proved properties, shows its inconsistency and compare it to the other estimators by an extensive simulation. Introduction...

A New Estimator of Entropy

In this paper we propose an estimator of the entropy of a continuous random variable. The estimator is obtained by modifying the estimator proposed by Vasicek (1976). Consistency of estimator is proved, and comparisons are made with Vasicek’s estimator (1976), van Es’s estimator (1992), Ebrahimi et al.’s estimator (1994) and Correa’s estimator (1995). The results indicate that the proposed esti...

A New Stochastic Restricted Biased Estimator under Heteroscedastic or Correlated Error

In this paper, under the linear regression model with heteroscedastic and/or correlated errors when the stochastic linear restrictions on the parameter vector are assumed to be held, a generalization of the ordinary mixed estimator (GOME), ordinary ridge regression estimator (GORR) and Generalized least squares estimator (GLSE) is proposed. The performance of this new estimator against GOME, GO...