By N. Balakrishnan, Enrique Castillo, Jose-Maria Sarabia Alegria

ISBN-10: 0817643613

ISBN-13: 9780817643614

ISBN-10: 0817644873

ISBN-13: 9780817644871

Barry Arnold has made basic contributions to many various parts of information, together with distribution thought, Bayesian inference, multivariate research, bounds and orderings, and characterization difficulties. prepared to honor Arnold’s major contributions to the sphere, this quantity is an outgrowth of the "International convention on Distribution conception, Order information, and Inference," held on the collage of Cantabria, Santander, Spain.

Several unusual and lively researchers spotlight a few of the fresh advancements in statistical distribution thought, order data and their homes, in addition to inferential tools linked to them. purposes to survival research, reliability, quality controls, and environmental difficulties are emphasised. the quantity is classed into the next 5 components, based on the focal point of the articles:

* Discrete distributions and applications

* non-stop distributions and applications

* Order facts and applications

* Reliability and applications

* Inference

This complete reference paintings will serve the statistical and utilized arithmetic groups, in addition to practitioners, researchers, and graduate scholars in utilized chance and facts, reliability engineering, and biostatistics.

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Extra info for Advances in Distribution Theory, Order Statistics, and Inference (Statistics for Industry and Technology)

Example text

Where's the lack of memory? Computational Statistics and Data Analysis, 18, 243-246. 114. Bayesian inference for conditionally specified models. In Proceedings of the Section on Bayesian Statistical Science, pp. 165-168, Annual Meeting of the American Statistical Association, Toronto, Ontario, Canada. Pu blications xxxiii 115. , S. P. Mukherjee, A. Chaudhure, and S. K. Basu), pp. 1-13. 116. El hombre mas alto del mundo (with J. A. Villasenor), Memoria del IX Foro Nactional de Estadistica^ pp. 113-115, Universidad Autonoma de Coahuila, Saltillo Coahuila, Mexico.

2001 157 Quantification of incompatability of conditional and marginal information (with E. Castillo and J. M. Sarabia), Communications in Statistics— Theory and Methods, 30, 381-395. 158. Modeling the lifetime of longitudinal elements (with M. Cantii-Sifuentes and J. A. Villasenor-Alva), Communications in Statistics—Simulation and Computation, 30, 717-741. 159. Beads, bags, Bayes, and the fundamental problem of sampling theory. Communications in Statistics—Theory and Methods, 30, 1963-1967. 160.

In some cases, the probabilities of success { p , p i , . . ,Pn} are all small, and hence a success is a rare event. For example, imagine a situation where one is testing for the occurrence of a rare disease in a country and where the prevalence in the i*^ geographical area is given by pi, while the overall prevalence in the country is given by p. In such a situation, we might be interested in observing just one (or at least one) success (individual with the disease in question), and hence might compare X (the number found with stratified testing with one selection from each of the geographical areas) and Y (the number found from a simple random sample of the whole area) by considering the probabilities of at least one success with each method.

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Advances in Distribution Theory, Order Statistics, and Inference (Statistics for Industry and Technology) by N. Balakrishnan, Enrique Castillo, Jose-Maria Sarabia Alegria

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