Advances on Methodological and Applied Aspects of Probability and - Statistic

This is one of two volumes that sets forth invited papers presented at the International Indian Statistical Association Conference. This volume emphasizes advancements in methodology and applications of probability and statistics. The chapters, representing the ideas of vanguard researchers on the topic, present several different subspecialties, including applied probability, models and applications, estimation and testing, robust inference, regression and design and sample size methodology. The text also fully describes the applications of these new ideas to industry, ecology, biology, health, economics and management. Researchers and graduate students in mathematical analysis, as well as probability and statistics professionals in industry, will learn much from this volume.

Sommario

Figures Part I: Applied Probability. Part II: Models and Applications. Part III: Estimation and Testing. Part IV: Robust Inference. Part V: Regression and Design. Part VI: Sample Size Methodology. Part VII: Applications to Industry. Part VIII: Applications to Ecology, Biology and Health. Part IX: Applications to Economics and Management.

Info autore

Balakrishnan; N. McMaster University, Ontario, Canada,

Riassunto

This is one of two volumes that sets forth invited papers from the International Indian Statistical Association Conference. This volume emphasizes advancements in methodology and applications of probability and statistics.

Dettagli sul prodotto

• Autori: N. Balakrishnan, N. (Mcmaster University Balakrishnan
• Con la collaborazione di: N. Balakrishnan (Editore)
• Editore: Taylor & Francis Ltd.
• Lingue: Inglese
• Formato: Tascabile
• Pubblicazione: 30.06.2020
• EAN: 9780367578510
• ISBN: 978-0-367-57851-0
• Pagine: 620
• Categorie: Scienze naturali, medicina, informatica, tecnica > Matematica > Teoria delle probabilità, stocastica, statistica matematica; MATHEMATICS / Probability & Statistics / General, MATHEMATICS / Probability & Statistics / Bayesian Analysis, Probability & statistics, Probability and statistics