In this book, an attempt has been made by developing some inferential methods for autoregressive models by using Internally studentized residuals.In the Applied regression analysis, the autoregressive models, moving average models and combined autoregressive and moving average models have a wide number applications. The study on autoregressive process/models is considered to be essential to both the theoretical and applied statisticians.The first order and higher order autoregressive models for regressed variable and errors have been described by giving auto covariance functions.Further, an...

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...

This book attempts to develope some new inferential procedures for time series regression models.An inferential method for a time series linear regression model with auto correlated disturbances using quarterly data, has been developed by proposing a test based on internally studentized residuals.Two modified estimation procedures have been proposed for time series regression models involving MA (1) and MA (q) process errors.Autoregressive moving averages and autoregressive conditionally heteroscadastic (ARCH) processesses have been specified systematically with their characteristics. The...

In the book an attempt has been made to develop some new diagnostic tests for statistical model building in the context of linear regression models. Diagnostics of outliers has been described and a test for identifying outliers by using predicted residuals has been proposed in the present study. Besides outliers, a measure of influence for diagnostics has been developed in the study. Some new modified R2 and criteria for model selection have been developed along with modified mean square prediction error criteria; and modified information criteria for model selection. A test for exogeneity in...

The bench mark to measure potential output is the data envelopment frontier determined by the best practice production units, which in the language of Data Envelopment Analysis (DEA) are called Decision Making Units (DMUs).In this book Chapter-I contains about the measurement of technical change in terms of total factor productivity growth and the contribution inputs growth to output growth. Chapter-II deals three important approaches namely, Parametric, Non-Parametric and Accounting approaches have been discussed for the measurement of technical change and technical progress. Chpater-III...

Efficiency rating of decision making units (DMUs) was long back identified as an important activity that helps both the producer and the policy maker. It requires that the DMUs are in competition, produce similar outputs combining similar inputs. Efficiency rating may be oriented or non-oriented. Twenty banks were considered to study efficiency variations pursuing output approach. For given inputs, outputs are radially projected onto the data envelopment frontier for each decision making unit. Frontier output augmentation is not possible for an efficient DMU, which is a commercial bank in the...

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....

Biostatistics or Biometrics is a growing filed of statistics. The word Biometrics derived from two Greek Words Bios (Life) and Matron (measurement). Thus Biometrics means measurement of life. Biostatistics may be defined as the quantitative analysis of biological phenomena based on the concurrent development of theory and observation related by appropriate methods of statistical inference .Chapter-I is any introductory one. It contains the general introduction about Biostatistics.Chapter-II describes the various aspects of Bioassays such as meaning, history and structure of...

In this present book Chapter-I is an introductory one. Chapter-II describes the various criteria for selection of regressors in the multiple regression analysis existing in this book. Chapter-III deals with the basic stepwise regression procedures for variable selection in multiple regression analysis and The mean square error of prediction criterion has been discussed along with a similar average estimated variance criterion for the selection of variables in the general linear model. Chapter-IV presents the various methods for choosing variable subsets in multiple linear regression analysis...