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Online Public Access Catalogue

题名/责任者:

Statistical regression and classification : from linear models to machine learning / Norman Matloff.

出版发行项:

Boca Raton, FL : CRC Press, Taylor & Francis Group, c2017

ISBN:

9781498710916

ISBN:

1498710913

ISBN:

9781138066465 :

ISBN:

113806646X

载体形态项:

xxxviii, 489 pages ; 25 cm.

丛编说明:

Chapman & Hall/CRC: Texts in Statistical Science Series

丛编统一题名:

Texts in statistical science.

个人责任者:

Matloff, Norman S., author.

论题主题:

Regression analysis.

论题主题:

Vector analysis.

中图法分类号:

O212

书目附注:

Includes bibliographical references and index.

摘要附注:

The book treats classical regression methods in an innovative, contemporary manner. Though some statistical learning methods are introduced, the primary methodology used is linear and generalized linear parametric models, covering both the Description and Prediction goals of regression methods. The author is just as interested in Description applications of regression, such as measuring the gender wage gap in Silicon Valley, as in forecasting tomorrow's demand for bike rentals. An entire chapter is devoted to measuring such effects, including discussion of Simpson's Paradox, multiple inference, and causation issues. Similarly, there is an entire chapter of parametric model fit, making use of both residual analysis and assessment via nonparametric analysis. --

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