Numerical Methods for Statistical Computation

Numerical Methods for Statistical Computation: Theory, Algorithms, and Applications bridges numerical analysis with modern statistics, offering a unified treatment of root-finding, linear systems, interpolation, integration, differential equations, and optimization all within a statistical framework. Through detailed theory, worked examples, and real applications, the book equips readers to solve complex statistical problems numerically. Designed for advanced undergraduates, graduate students, and researchers in statistics and data science, it emphasizes both algorithmic understanding and statistical insight. With a strong pedagogical structure and extensive example sets, this book serves as a comprehensive resource for statistical computation in theory and practice.

Autorentext

Dr. Janardan Behera is a researcher and educator specializing in numerical analysis and statistical computation. His work bridges mathematical theory and computational practice, with a focus on solving data-driven problems using algorithmic methods.Prof. S.K. Sahu is a senior academic with extensive experience in applied mathematics and statistics.