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Fitting Linear Models Application by Mcintosh (6 results)
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Condition: Good. Volume 10. This is an ex-library book and may have the usual library/used-book markings inside.This book has soft covers. In good all round condition. Please note the Image in this listing is a stock photo and may not match the covers of the actual item,400grams, ISBN:0387907467.
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Fitting linear models : an application of conjugate gradient algorithms. Allen McIntosh / Lecture notes in statistics ; 10
Language: English
Published by New York ; Heidelberg ; Berlin : Springer, 1982
ISBN 10: 0387907467 ISBN 13: 9780387907468
(Berlin, Condition: Gut. IV, 200 S. : graph. Darst. ; 24 cm Sprache: Englisch Gewicht in Gramm: 480 Softcover reprint of the original 1st ed. 1982.
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Fitting Linear Models: An Application of Conjugate Gradient Algorithms (Lecture Notes in Statistics, 10)
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
£ 50.43
£ 11.98 shipping
Ships from United Kingdom to U.S.A.Quantity: Over 20 available
Add to basketCondition: New. In.
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PF. Condition: New.
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Paperback. Condition: Brand New. 200 pages. 9.25x6.10x0.47 inches. In Stock.
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Fitting Linear Models : An Application of Conjugate Gradient Algorithms
Language: English
Published by Springer, Copernicus, 1982
ISBN 10: 0387907467 ISBN 13: 9780387907468
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The increasing power and decreasing price of smalI computers, especialIy 'personal' computers, has made them increasingly popular in statistical analysis. The day may not be too far off when every statistician has on his or her desktop computing power on a par with the large mainframe computers of 15 or 20 years ago. These same factors make it relatively easy to acquire and manipulate large quantities of data, and statisticians can expect a corresponding increase in the size of the datasets that they must analyze. Unfortunately, because of constraints imposed by architecture, size or price, these smalI computers do not possess the main memory of their large cousins. Thus, there is a growing need for algorithms that are sufficiently economical of space to permit statistical analysis on smalI computers. One area of analysis where there is a need for algorithms that are economical of space is in the fitting of linear models.
