In this book an attempt has been made by proposing some inferential techniques for linear regression models by using various types of residuals other than OLS residuals.Chapter I contains the general introduction about the concept of residuals in regression analysis. Various types of residuals and their properties have been described in chapter II. The literature on residual analysis and regression diagnostics have been reviewed in chapter III. In particular, it is discussed about examination of residual plots diagnostics for identifying unusual data points, detection of influential subsets, until applications of residuals. Chapter IV contains the proposed methods under is the contributory one in which outliers are detected; Leverage and influential points are identified; Goldfeld-Quandt test statistics computed to know the heteroscodastocity; Chow test statistic is computed to know the structural change and Durbin-Waston test statistic is competed to know the autocorrelation using different types of residuals.

In The present book Chapter - I is an introductory one. It contains the general introduction about the problem of forecasting besides objectives and organization of the research.Chapter - II describes the various basic forecasting models such as Naive, Moving averages, Simple smoothing, Double moving averages and Double smoothing, triple smoothing and adaptive smoothing forecasting models. Chapter - III deals with the Adaptive, Filtering and Combination for forecasting techniques. Chapter - IV gives the need for exponential smoothing forecasting model along with model selection criterion. Chapter - V presents the presents the various autoregressive forecasting models such as ARMA, ARIMA and STARMA models with their link with dynamic linear models .Chapter - VI proposes some new forecasting techniques in econometrics. Chapter - VII epitomizes the conclusions based on the present book..Several relevant articles regarding the forecasting techniques have been presented under a separate title 'BIBLIOGRAPHY'.

In this book, an attempt has been made to propose some new estimation procedures for the linear regression models such as elemental slopes methods, Grouping method, Hat diagonals method, and Dispersion and Correlation methods for estimating for estimating the parameters of the linear regression models. The proposed methods have been applied to two and three variables linear models for their validity.In this book Introduction given in the Chapter I, some important existing estimation procedures such as OLS, GLS, WLS, RLS and ML have been described in Chapter II. A brief about the review of the literature has been described in chapter III. In Chapter IV, some new estimation methods namely Elemental Slopes method, Grouping method, Hat diagonals method and Dispersion and Corrrelation methods have been proposed and applied to two and three variables linear models for their validity. The summary and conclusions besides the suggestions for future research, have been give in Chapter V.The slected list of research articles has been presented under Bibliography.