A modification of the Gauss-Jordan procedure as an adequate alternative to iterative procedures in multiple regression

Digitized by Kansas Correctional Industries

Bibliographic Details
Main Author: Hildebrand, Melvin
Language:en_US
Published: Kansas State University 2011
Online Access:http://hdl.handle.net/2097/7456
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spelling ndltd-KSU-oai-krex.k-state.edu-2097-74562019-03-06T15:51:20Z A modification of the Gauss-Jordan procedure as an adequate alternative to iterative procedures in multiple regression Hildebrand, Melvin Digitized by Kansas Correctional Industries 2011-02-21T15:56:48Z 2011-02-21T15:56:48Z 1970 1970 2010 Thesis http://hdl.handle.net/2097/7456 en_US This volume was digitized and made accessible online due to deterioration of the original print copy. If you are the author of this work and would like to have online access removed, please contact the Library Administration Office, 785-532-7400, library@k-state.edu. Kansas State University
collection NDLTD
language en_US
sources NDLTD
description Digitized by Kansas Correctional Industries
author Hildebrand, Melvin
spellingShingle Hildebrand, Melvin
A modification of the Gauss-Jordan procedure as an adequate alternative to iterative procedures in multiple regression
author_facet Hildebrand, Melvin
author_sort Hildebrand, Melvin
title A modification of the Gauss-Jordan procedure as an adequate alternative to iterative procedures in multiple regression
title_short A modification of the Gauss-Jordan procedure as an adequate alternative to iterative procedures in multiple regression
title_full A modification of the Gauss-Jordan procedure as an adequate alternative to iterative procedures in multiple regression
title_fullStr A modification of the Gauss-Jordan procedure as an adequate alternative to iterative procedures in multiple regression
title_full_unstemmed A modification of the Gauss-Jordan procedure as an adequate alternative to iterative procedures in multiple regression
title_sort modification of the gauss-jordan procedure as an adequate alternative to iterative procedures in multiple regression
publisher Kansas State University
publishDate 2011
url http://hdl.handle.net/2097/7456
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