Abstract In the Inverse Gaussian Regression (IGR), there is a significant increase in the
variance of the commonly used Maximum Likelihood (ML) estimator in the presence of …

A well‐known concern regarding the usual linear regression model is multicollinearity. As
the strength of the association among the independent variables increases, the squared …

Introduction Increasing urban population and traffic density on one side and rising hospital
demands on the other has underlined the importance of transportation modeling. In this …

The demand for healthcare facilities in the world is growing daily, and this growth in demand
exceeds general population growth. This situation has made hospital trips a vital issue …

The ridge regression estimator produces efficient estimates than the Ordinary Least Square
Estimator in a linear regression model that has multicollinearity problem. However, the …

Tüm dünyada ulaştırma yatırımlarına verilen önem her geçen gün artmaktadır. Bu nedenle,
etkin planlama gerek yeni ulaşım yatırımlarında gerekse mevcut ulaşım sisteminin …

Linear regression is the measure of relationship between two or more variables known as
dependent and independent variables. Classical least squares method for estimating …

Ordinary least squares (OLS) offers good parameter estimates in regression if all
assumptions are met. However, if the assumptions are not adhered to due to the presence of …

The lack of certain assumptions is common in ordinary least squares regression models
whenever there is/are outliers and high leverage in the observations with an extreme value …

Genel lineer regresyon modellerinde, çoklu doğrusal bağlantının varlığı durumunda, en
küçük kareler (EKK) yöntemi kullanıldığında parametre tahminleri kararsız ve yüksek …