Hybrid Censoring: Models, Methods and Applications for Engineering and Bio Health focuses on hybrid censoring, a specific yet important topic in censoring methodology that has numerous applications. Readers will find information on the significance of censored data in theoretical and applied contexts and descriptions of extensive data sets from life-testing experiments where these forms of data naturally occur. The existing literature on censoring methodology, life-testing procedures, or lifetime data analysis provides only hybrid censoring schemes, with little information about hybrid censoring methodologies, ideas, and statistical inferential methods. This book fills that gap by providing readers with valuable information on these topics. The statistical tools presented are applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. Presents many numerical examples to adequately illustrate all the inferential methods discussed Provides open problems and possible directions for future work Reviews developments pertaining to Type-II HCS, and includes the most recent research and trends Explains why the hybrid censored sampling is important Provides detail in using HCS under different settings and the designs of HCS Includes R code on website for ease of use

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