A Principal-component Missing-data Method for Multiple Regression Models

A Principal-component Missing-data Method for Multiple Regression Models
Author: Robert Ernest Dear
Publisher:
Total Pages: 86
Release: 1959
Genre: Analysis of variance
ISBN:


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A Principal-component Missing-data Method for Multiple Regression Models
Language: en
Pages: 86
Authors: Robert Ernest Dear
Categories: Analysis of variance
Type: BOOK - Published: 1959 - Publisher:

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Principal Component Analysis
Language: en
Pages: 283
Authors: I.T. Jolliffe
Categories: Mathematics
Type: BOOK - Published: 2013-03-09 - Publisher: Springer Science & Business Media

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Principal component analysis is probably the oldest and best known of the It was first introduced by Pearson (1901), techniques ofmultivariate analysis. and dev
Flexible Imputation of Missing Data, Second Edition
Language: en
Pages: 444
Authors: Stef van Buuren
Categories: Mathematics
Type: BOOK - Published: 2018-07-17 - Publisher: CRC Press

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Missing data pose challenges to real-life data analysis. Simple ad-hoc fixes, like deletion or mean imputation, only work under highly restrictive conditions, w
Places Rated Almanac
Language: en
Pages: 452
Authors: David Savageau
Categories: Philosophy
Type: BOOK - Published: 1993 - Publisher: Prentice Hall

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This sometimes controversial bestseller, completely updated with all new statistics, is packed with timely facts and unbiased information on more than 300 metro
Feature Engineering and Selection
Language: en
Pages: 266
Authors: Max Kuhn
Categories: Business & Economics
Type: BOOK - Published: 2019-07-25 - Publisher: CRC Press

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The process of developing predictive models includes many stages. Most resources focus on the modeling algorithms but neglect other critical aspects of the mode