Applied Probability and Statistical Inference in Reliability Engineering

ISBN 10: 372588305X / ISBN 13: 9783725883059

Published by MDPI AG, 2026

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - The present reprint contains the 11 articles accepted and published in the Special Issue 'Applied Probability and Statistical Inference in Reliability Engineering, 2025' of the MDPI Mathematics journal, which cover a wide range of topics connected to recent methodological developments and emerging applications at the intersection of probabilistic modeling and reliability analysis. These topics include, among others, advanced probabilistic and distributional modeling for nonstandard data (including censoring, skewness, dependence, and imprecision), as well as statistical estimation and inference methods in reliability analysis. It further addresses system reliability, stochastic processes (including renewal and aging phenomena), stochastic ordering, data-driven approaches, and the integration of reliability modeling with maintenance optimization and decision-making.It is hoped that this reprint will be of interest and value to researchers working in Applied Probability and Statistical Inference in Reliability Engineering, as well as to readers with a solid mathematical background who wish to become acquainted with recent advances in probabilistic modeling, statistical methodology and their applications in reliability analysis across diverse domains.

Seller Inventory # 9783725883059

Bibliographic Details

• Title: Applied Probability and Statistical Inference in Reliability Engineering
• Publisher: MDPI AG
• Publication Date: 2026
• Language: English
• ISBN 10: 372588305X
• ISBN 13: 9783725883059
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 21D millimeters 250 millimeters width by 175 millimeters height by 21 millimeters depth
• Weight: 820 grams

About this title

Synopsis

The present reprint contains the 11 articles accepted and published in the Special Issue "Applied Probability and Statistical Inference in Reliability Engineering, 2025" of the MDPI Mathematics journal, which cover a wide range of topics connected to recent methodological developments and emerging applications at the intersection of probabilistic modeling and reliability analysis. These topics include, among others, advanced probabilistic and distributional modeling for nonstandard data (including censoring, skewness, dependence, and imprecision), as well as statistical estimation and inference methods in reliability analysis. It further addresses system reliability, stochastic processes (including renewal and aging phenomena), stochastic ordering, data-driven approaches, and the integration of reliability modeling with maintenance optimization and decision-making.

It is hoped that this reprint will be of interest and value to researchers working in Applied Probability and Statistical Inference in Reliability Engineering, as well as to readers with a solid mathematical background who wish to become acquainted with recent advances in probabilistic modeling, statistical methodology and their applications in reliability analysis across diverse domains.