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Mathematical and Statistical Models and Methods in Reliability


Mathematical and Statistical Models and Methods in Reliability

Applications to Medicine, Finance, and Quality Control
Statistics for Industry and Technology

von: V.V. Rykov, N. Balakrishnan, M.S. Nikulin

CHF 200.50

Verlag: Birkhäuser
Format: PDF
Veröffentl.: 02.11.2010
ISBN/EAN: 9780817649715
Sprache: englisch
Anzahl Seiten: 457

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Beschreibungen

The book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability. Written by renowned experts in the field of reliability, the contributions cover a wide range of applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation.
Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.
Written by renowned experts in the field of reliability, this book deals with various aspects of mathematical and statistical models and methods in reliability. The contributions cover a wide range of applications and reflect recent developments.
Reliability Models, Methods, and Optimization.- Reliability of Semi-Markov Systems with Asymptotic Merging Phase Space.- Nonlinearly Perturbed Stochastic Processes and Systems.- On a Copula for Failure Times of System Elements.- On One Method of Reliability Coefficients Calculation for Objects in Non-Homogeneous Event Flows.- A New Approach to Maintenance Optimization by Modeling Intensity Control.- Longitudinal Latent Markov Processes Observable Through an Invariant Rasch Model.- Dynamics of Dependence Properties for Lifetimes Influenced by Unobservable Environmental Factors.- On Alternative of Choice for a Prophylaxis Problem.- Optimal Incomplete Maintenance for Systems with Discrete Time-to-Failure Distribution.- A Gini-Type Index for Aging/Rejuvenating Objects.- Redundancy Analysis for Multi-state System: Reliability and Financial Assessment.- On the Reliability Modeling of Hierarchical Systems.- Statistical Methods in Reliability.- Parametric Estimation of Redundant System Reliability From Censored Data.- Assessing Accuracy of Statistical Inferences by Resamplings.- Change Point Estimation in Regression Models with Fixed Design.- A Model for Field Failure Prediction Using Dynamic Environmental Data.- Efficient Regression Estimation Under General Censoring and Truncation.- On Generalized Tests of Fit for Multinomial Populations.- Modeling and Scaling of Categorical Data.- Nonparametric Estimation and Testing the Effect of Covariates in Accelerated Life Time Models Under Censoring.- Nonparametric Estimation of Time Trend for Repairable Systems Data.- Confidence Region for Distribution Function from Censored Data.- Empirical Estimate with Uniformly Minimal d-Risk for Bernoulli Trials Success Probability.- Estimation of Archival Lifetime Distribution for Writable Optical Disks from Accelerated Testings.- Applications.- Ages in Reliability and Bio Systems, Interpretations, Control, and Applications.- Shocks in Mixed Populations.- Bayesian Estimation of Degradation Model Defined by a Wiener Process.- Benefits of Threshold Regression: A Case-Study Comparison with Cox Proportional Hazards Regression.- Optimal Stopping and Reselling of European Options.- Bayesian Modeling of Health State Preferences.- Information Measures in Biostatistics and Reliability Engineering.- Reliability Computer Tools.- Software System for Simulation and Research of Probabilistic Regularities and Statistical Data Analysis in Reliability and Quality Control.- Inverse Gaussian Model and Its Applications in Reliability and Survival Analysis.
An outgrowth of the sixth conference on “Mathematical Methods in Reliability: Theory, Methods, and Applications,” this book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability.
Written by recognized experts in the field of reliability, the contributions cover a wide range of models, methods, and applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation.
The volume is thematically organized into four major sections:
* Reliability Models, Methods, and Optimization;
* Statistical Methods in Reliability;
* Applications;
* Computer Tools for Reliability.
Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.
Real-world applications to survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportationChapters are written by recognized experts in reliabilityFor a broad audience of researchers and practitioners in applied probability and statistics and a variety of related fields
The book is a selection of invited chapters, all of which deal with various aspects of mathematical and statistical models and methods in reliability. Written by renowned experts in the field of reliability, the contributions cover a wide range of applications, reflecting recent developments in areas such as survival analysis, aging, lifetime data analysis, artificial intelligence, medicine, carcinogenesis studies, nuclear power, financial modeling, aircraft engineering, quality control, and transportation.
Mathematical and Statistical Models and Methods in Reliability is an excellent reference text for researchers and practitioners in applied probability and statistics, industrial statistics, engineering, medicine, finance, transportation, the oil and gas industry, and artificial intelligence.

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