9781584881742-1584881747-Statistical Modelling with Quantile Functions

Statistical Modelling with Quantile Functions

ISBN-13: 9781584881742
ISBN-10: 1584881747
Edition: 1
Author: Gilchrist, Warren
Publication date: 2000
Publisher: Chapman and Hall/CRC
Format: Hardcover 344 pages
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Book details

ISBN-13: 9781584881742
ISBN-10: 1584881747
Edition: 1
Author: Gilchrist, Warren
Publication date: 2000
Publisher: Chapman and Hall/CRC
Format: Hardcover 344 pages

Summary

Acknowledged authors Gilchrist, Warren wrote Statistical Modelling with Quantile Functions comprising 344 pages back in 2000. Textbook and eTextbook are published under ISBN 1584881747 and 9781584881742. Since then Statistical Modelling with Quantile Functions textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

Galton used quantiles more than a hundred years ago in describing data. Tukey and Parzen used them in the 60s and 70s in describing populations. Since then, the authors of many papers, both theoretical and practical, have used various aspects of quantiles in their work. Until now, however, no one put all the ideas together to form what turns out to be a general approach to statistics.

Statistical Modelling with Quantile Functions does just that. It systematically examines the entire process of statistical modelling, starting with using the quantile function to define continuous distributions. The author shows that by using this approach, it becomes possible to develop complex distributional models from simple components. A modelling kit can be developed that applies to the whole model - deterministic and stochastic components - and this kit operates by adding, multiplying, and transforming distributions rather than data.

Statistical Modelling with Quantile Functions adds a new dimension to the practice of statistical modelling that will be of value to anyone faced with analyzing data. Not intended to replace classical approaches but to supplement them, it will make some of the traditional topics easier and clearer, and help readers build and investigate models for their own practical statistical problems.

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