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portada Sharp Inequalities for Ordered Random Variables in Statistics and Reliability: Volume 2: Advanced Models and Applications
Type
Physical Book
Year
2027
Language
English
Format
Hardcover
Dimensions
23.5x15.5 cm
ISBN13
9783032387363

Sharp Inequalities for Ordered Random Variables in Statistics and Reliability: Volume 2: Advanced Models and Applications

Narayanaswamy Balakrishnan (Author) · Springer Nature Switzerland · Hardcover

Sharp Inequalities for Ordered Random Variables in Statistics and Reliability: Volume 2: Advanced Models and Applications - Narayanaswamy Balakrishnan

New Book Imported to Taiwan
Delivery: 27 Jan - 11 Feb Shipping: 71 to 77 business days.
NT$ 8,562
NT$ 8,562

Synopsis "Sharp Inequalities for Ordered Random Variables in Statistics and Reliability: Volume 2: Advanced Models and Applications"

This second volume, similar to the first volume, discusses various inequalities and sharp bounds for some general forms of ordered data as well as some functions of them. In particular, different bounds and their sharpness are discussed for order statistics from identically distributed and exchangeable samples, order statistics from arbitrarily distributed variable, coherent and mixed reliability systems, record values and their extensions, generalized order statistics and finally mixtures of ordered distributions. An elaborate numerical evaluation and comparison of various bounds are also presented to illustrate their inherent differences and their accuracy and precision. Moreover, their applications to inference and reliability are also highlighted. This second and final volume provides an in-depth exposure to various mathematical inequalities and bounds established historically as well as in recent years and their applications to various forms of ordered data and some important functions of them like range, L-statistics and trimmed mean. It thus presents an up-to-date discussion of all results in this important area of mathematical and statistical research. The results described here are general and so would be useful in other areas of Probability and Statistics as well.

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