Statistical Methods and Practice: Recent Advances

Statistical methods serve as valuable tools in business, health and industry. Statistical problems formulated in different ways allow the user to make appropriate types of decisions in these applications. This volume contains contributions from acknowledged experts in different aspects of statistical theory and applications with a goal to: Review recent developments. Focus on and highlight some new results and applications. Suggests some interesting possible new directions for research. This carefully edited volume, divided into seven parts – General, Distribution Theory, Inference, Outliers and Robust Inference, Design of Experiments, Survival Analysis and Reliability and Applied Probability will benefit both the student and researcher.

Table of Contents:
Preface List of Contributors List of Tables Part 1. General: Statistical Proofs of Some Matrix Theorems Part II:Distribution Theory: Distributions in Given Parametric Families Most Nearly Compatible with Given Conditional Information Some Properties of the Matrix Generalized Inverse Gaussian Distribution On a General Multivariate Dirichlet Density and it’s Applications Part III. Inference: Estimation in a Gompertzian Stochastic Model Simultaneous Equivariant Estimation of the Parameters of Uniform Models Based on Progressive Type II Right Censored Sample Best Unbiased Predictor with Respect to Convex Loss Function Limits of Bayes Estimates of Estimable Parameters Some Exact Results in Sequential Fixed – width Interval Estimation of Location Parameter of Exponential Distribution Selecting the Normal Population with the Largest Mean: A Restricted Subset Selection Rule Estimation of the Number of Signals in the Uniform Linear Array Model Quadratic Discriminant Function: Estimation of Probability of Misclasssification Part IV. Outliers and Robust Inference: Outlier – Robust Estimation of the Mean of an Exponential Distribution Under the Presence of Multiple Outliers The Hermitian Estimator of the Quantile Function: Implications for the M- Estimation of Location Part V. Design of Experiments: Discrete Structure of Group Divisible Designs with g = l1 + 2 and h = 4 E-Optimality and Group Divisible Designs Optimum and Restricted-Optimum Designs for Multivariate Time-Series Experiments Interval Estimation of Variance Components in Triallel Model Improved Estimators of Variance Components in Diallel Model Part VI. Survival Analysis and Reliability: Analysis of Incomplete Data in Presence of Dependent Competing Risks Reliability Modelling in Bivariate Pearson System Part VII. Applied Probability: A Continuous Review Perishable Inventory System with Poisson Demand and Partial Backlogging Subject Index Author Index

About the Author :
N. Balakrishnan.: Department of Mathematics & Statistics McMaster University, Hamilton, Ontario, Canada M. R. Srinivasan.: Department of Statistics, University of Madras Chennai 600 005 N. Kannan.: Department of Management Sciences & Statistics University of Texas at San Antonio, Texas, USA