The textbook Statistical Inference: Theory of Estimation by Manoj Kumar Srivastava, Abdul Hamid Khan, and Namita Srivastava is a comprehensive guide tailored for postgraduate students and competitive exam aspirants. Published by PHI Learning, it serves as a sequel to their earlier work on the testing of hypotheses. Core Themes and Content
Consistency, Consistent Asymptotic Normality (CAN), and Best Asymptotic Normality (BAN). Bayes & Minimax Statistical Inference By Manoj Kumar Srivastava Pdf
The second pillar, Statistical Inference: Testing of Hypotheses, focuses on the methodology of reaching conclusions about population parameters based on sample data. The textbook Statistical Inference: Theory of Estimation by
: Finding Pitman estimators for location and scale models by exploiting model symmetry. Book Structure (Table of Contents) Introduction Data Summarization and Principle of Sufficiency Unbiased Estimation Information Inequality Asymptotic Theory and Consistency Methods of Estimation Principle of Equivariance Bayes and Minimax Estimation Confidence Interval Estimation Key Features Self-Contained Chapters : Each chapter is supplemented with numerous solved problems and exercises framed at varying difficulty levels. Exam Prep Utility : Highly recommended by reviewers on Bayes & Minimax The second pillar, Statistical Inference: