In the Present Book Chapter - I is an introductory one. It contains the general introduction about the problem of testing linear restrictions on the parameters of the linear regression models, Chapter - II describes the concept and the estimation of parameters of linear model subject to the linear restrictions. Chapter - III deals with the review about the various tests for linear restrictions in the linear statistical models including Wald, Likelihood Ratio and Lagrange Multiplier tests. Chapter - IV gives the details about the various problems of testing equality between sets of regression coefficients in linear regression models, Chapter - V proposes some new criteria for testing linear restrictions on parameters in linear statistical models. Chapter - VI presents the conclusions. Several selected references for the present research work have been given under the title "BIBLIOGRAPHY."

This book has brought out the current estimation methods, stressing the basic inferential methods and discussing the various related problems arising in applying the methods to SURE models. Firstly, the SURE model with first-order scalar autoregressive errors; secondly, an Estimation procedure has been developed for SURE model with first-order scalar autoregressive errors; thirdly, the SURE model with first-order vector autoregressive errors has been specified and a new inferential techniques has been developed for its estimation; fourthly, an adaptable Ridge Regression estimation technique has been proposed for the SURE model under the problem of multicollinearity; finally, two new test procedures have been developed for testing nested and non-nested general linear hypotheses about the parameters to the SURE modeLS