Lifetime Analysis by Aging Intensity Functions [electronic resource] /
Szymkowiak, Magdalena.author.
This book addresses a range of aging intensity functions, which make it possible to measure and compare aging trends for lifetime random variables. Moreover, they can be used for the characterization of lifetime distributions, also with bounded support. Stochastic orders based on the aging intensities, and their connections with some other orders, are also discussed. To demonstrate the applicability of aging intensity in reliability practice, the book analyzes both real and generated data. The estimated, properly chosen, aging intensity function is mainly recommended to identify data's lifetime distribution, and secondly, to estimate some of the parameters of the identified distribution. Both reliability researchers and practitioners will find the book a valuable guide and source of inspiration.
Basic reliability functions -- Aging intensity of nonnegative univariate absolutely continuous Distributions -- Aging intensities of discrete distributions -- Aging intensities vector for bivariate absolutely continuous distributions -- Aging intensities vectors for bivariate discrete distributions -- Generalized aging intensity functions -- G-generalized aging intensity functions -- Support dependent G-generalized aging intensity functions -- Conclusions and Final Remarks.
This book addresses a range of aging intensity functions, which make it possible to measure and compare aging trends for lifetime random variables. Moreover, they can be used for the characterization of lifetime distributions, also with bounded support. Stochastic orders based on the aging intensities, and their connections with some other orders, are also discussed. To demonstrate the applicability of aging intensity in reliability practice, the book analyzes both real and generated data. The estimated, properly chosen, aging intensity function is mainly recommended to identify data's lifetime distribution, and secondly, to estimate some of the parameters of the identified distribution. Both reliability researchers and practitioners will find the book a valuable guide and source of inspiration.
Computational intelligence.
Engineering-Data processing.
Engineering mathematics.
Computational Intelligence.
Data Engineering.
Engineering Mathematics.