A Computational Approach to Statistical Learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods.
The text contains annotated code to over 80 original ref.
Johnn Taylor
Taylor B. Barton
Arnold, Michael
Ross Taylor
Our railways have witnessed many different types of passenger train in the recent past.
David Arnold
David Arnold
Ken Arnold
Targeted at intermediate-to-advanced developers, this is the definitive tutorial introduction and reference to the java se7 language and its essential libraries.
Arnold, Michael
Posted to the hostile territory of dartmoor, captain innocent stryker and his men are attacked by an elite cavalry unit commanded by the formidable colonel gabriel wild and suffer heavy losses.
Tristan Taylor
Danielle Taylor
Arnold Neumaier
The de gruyter studies in mathematical physics are devoted to the publication of monographs and high-level texts in mathematical physics.
Rashawna Taylor
Lulu Taylor
M. Taylor Lauritsen
Andrew Arnold
Seamus Taylor
Philip P. Arnold
Philip P. Arnold
Tess Taylor
Arnold Berleant
Taylor Randolph
Sean Taylor
Zachary Taylor
Peter R. Taylor
Agnes Arnold-Forster
Philip P. Arnold
Liza Taylor
Agnes Arnold-Forster
Andrew Taylor
Christine Taylor-Butler
Goldie Taylor
Tony Taylor
Lawanda Taylor
Jeff C. Jeff C Taylor
Taylor N. Carlson
Taylor Eggan
Taylor, Stephen
Sharon Estill Taylor
Arnold Bennett
James Stacey Taylor
Caroline Arnold
Taylor Vander Leest
Tom Taylor
Barbara Taylor Bradford
Alice Taylor
M. Taylor Madsen
R. Douglas Arnold
Cat Taylor
Taylor publishing
Arnold Bennett
Jeff C. Jeff C Taylor
Arnold Bennett
Taylor, Lee
Emily J. Taylor
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Brad Taylor
Clive Alando Taylor
Lisa B. Taylor
Sarah Todd Taylor
Michael Gil
Intended for specialists in functional analysis and stability theory, this work presents a systematic exposition of estimations for norms of operator-valued functions, and applies the estimates to spectrum perturbations of linear operators and stability t.
Taylor Arnold
A computational approach to statistical learning gives a novel introduction to predictive modeling by focusing on the algorithmic and numeric motivations behind popular statistical methods.
Markus Frhlich
John Olusegun Ogundare
Provides a modern approach to least squares estimation and data analysis for undergraduate land surveying and geomatics programsrich in theory and concepts, this comprehensive book on least square estimation and data analysis provides e.
Masafumi Akahira
Zhengming Wang
Measurement data modeling and parameter estimation integrates mathematical theory with engineering practice in the field of measurement data processing.
Andreas Quatember
This book emphasizes that artificial or pseudo-populations play an important role in statistical surveys from finite universes in two manners: firstly, the concept of pseudo-populations may substantially improve users understand.
J. N. K. Rao
Praise for the first edition "this pioneering work, in which rao provides a comprehensive and up-to-date treatment of small area estimation, will become a classic...
Harry L. Van Trees
Harry L. Van Trees
Hani S. Mahmassani
John E. Doherty
Adriaan van den Bos
The subject of this book is estimating parameters of expectation models of statistical observations.
Jiti Gao
Useful in the theoretical and empirical analysis of nonlinear time series data, semiparametric methods have received extensive attention in the economics and statistics communities over the past twenty years.
Jean-Claude Bertein
Richard M. Royall
George B. Dresser
Efi Pagitsas
William T. Steffens
Betty S. Kwok
Patricia Ann Tracey
Dennis J. Aigner
Harry Bridgman Pulsifer