Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications

ISBN-13: 9780367715113 / Angielski / Twarda / 2022 / 246 str.

Samanta, Debabrata

Opis

This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements.

Spis treści

Part 1: Statistical Computing. 1. Computational Arithmetic for Statistical Computation. 2. Numerical Algorithm and Software for Statistical Computation. 3. Impact of Modern Computer on Statistical Computing. 4. Numerical Methods as the Backbone of Simulation Techniques. 5. Linear Algebra and Optimization for Computation. 6. Role of Transformation Functions in Restructuring the Problem Statements. 7. Optimization of Computing Resources. 8. Role of Statistical Graphics in Data Analysis. Part 2: Statistical Methodology. 9. Computationally Intensive Statistical Methods. 10. Techniques in Computational Inferencing. 11. Computer Models for Design of Experiments. 12. Bayesian Analysis for Computational Inference. 13. Survival Analysis Models in Computational Methods. 14. Impact of Data Mining to the Computational Statistics for Machine Learning. Part 3: Computational Statistics Applications. 15. Computational Statistics in Finance and Economics. 16. Computationally Intensive Statistical Methods in Human Biology. 17. Computational Statistics within Clinical Research. 18. Computational Statistics for Network Security.