Statistical Degradation Data Analysis: Semiparametric and Nonparametric Stochastic Process Approaches (Emerging Topics in Statistics and Biostatistics)

This book provides a systematic treatment of efficient methods for modeling, analyzing, and designing degradation tests, with particular emphasis on stochastic-process-based semiparametric and nonparametric approaches motivated by practical applications.Statistical Degradation Data Analysis: Semiparametric and Nonparametric Stochastic Process Approaches compares parametric, semiparametric, and nonparametric methods through Monte Carlo simulation studies and real data examples, and demonstrates how these methodologies can be applied across a range of disciplines.The book also discusses extensions and open problems in this area. In engineering and the sciences, degradation refers to the gradual and irreversible decline in the performance, reliability, or remaining life of a system or asset. Because many systems are equipped with sensors that collect degradation measurements over time, statistical degradation modeling plays an important role in understanding the evolution of such processe