Continuum regression and examining related regression models

Regression analysis is a common statistical method used in various scientific disciplines in order to search and model the relationships among variables. For this purpose, firstly estimation of regression coefficients are dealt with and the oldest known method is the least squares method. However, linear least squares estimated coefficients are affected from the multicollinearity problem arises when there is a linear relationship between the explanatory variables. In this case, alternative estimation methods are used. In this study, ridge regression, principle component regression, partial least squares regression and continuum regression methods among the estimation methods are used in case of multicollinearity problem and the relationships between these methods have been examined. For this purpose, the data set in Fearn (1983) is exemplified.