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Nonparametric Model Selection


Nonparametric Model Selection
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Nonparametric Model Selection


Nonparametric Model Selection
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Author : Maurizio Tiso
language : en
Publisher:
Release Date : 1999

Nonparametric Model Selection written by Maurizio Tiso and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.




Model Selection For Nonparametric Regression


Model Selection For Nonparametric Regression
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Author : Yuhong Yang
language : en
Publisher:
Release Date : 1997

Model Selection For Nonparametric Regression written by Yuhong Yang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with categories.




Nonparametric Estimation And Model Selection Using Constrained Splines In Linear Inversion Problems


Nonparametric Estimation And Model Selection Using Constrained Splines In Linear Inversion Problems
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Author : Davide Verotta
language : en
Publisher:
Release Date : 1992

Nonparametric Estimation And Model Selection Using Constrained Splines In Linear Inversion Problems written by Davide Verotta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1992 with categories.




Variable Selection In Non Parametric Regression


Variable Selection In Non Parametric Regression
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Author : Pʻing Chang
language : en
Publisher:
Release Date : 1990

Variable Selection In Non Parametric Regression written by Pʻing Chang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1990 with categories.




Model Selection Uniform Inference And Nonparametric Regression


Model Selection Uniform Inference And Nonparametric Regression
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Author : Alexis De Boeck
language : en
Publisher:
Release Date : 2019

Model Selection Uniform Inference And Nonparametric Regression written by Alexis De Boeck and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.




New Techniques For Functional Data Analysis


New Techniques For Functional Data Analysis
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Author : Matthew Rogers Avery
language : en
Publisher:
Release Date : 2012

New Techniques For Functional Data Analysis written by Matthew Rogers Avery and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.




Data Analysis And Approximate Models


Data Analysis And Approximate Models
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Author : Patrick Laurie Davies
language : en
Publisher: CRC Press
Release Date : 2014-07-07

Data Analysis And Approximate Models written by Patrick Laurie Davies and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-07 with Mathematics categories.


The First Detailed Account of Statistical Analysis That Treats Models as ApproximationsThe idea of truth plays a role in both Bayesian and frequentist statistics. The Bayesian concept of coherence is based on the fact that two different models or parameter values cannot both be true. Frequentist statistics is formulated as the problem of estimating



Appendix


Appendix
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Author : Vivek F. Farias
language : en
Publisher:
Release Date : 2012

Appendix written by Vivek F. Farias and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012 with categories.


This document presents supporting materials for the following publication: Farias, Jagabathula and Shah (2012), 'A Nonparametric Approach to Modeling Choice with Limited Data,' Management Science, Articles in Advance, pp. 1-18. Choice models are today ubiquitous across a range of applications in operations and marketing. Real world implementations of many of these models face the formidable stumbling block of simply identifying the 'right' model of choice to use. Since models of choice are inherently high dimensional objects, the typical approach to dealing with this problem is positing, a-priori, a parametric model that one believes adequately captures choice behavior. This approach can be substantially sub-optimal in scenarios where one cares about using the choice model learned to make fine-grained predictions; one must contend with the risks of mis-specification and over/under-fitting. Thus motivated, we visit the following problem: For a 'generic' model of consumer choice (namely, distributions over preference lists) and a limited amount of data on how consumers actually make decisions (such as marginal information about these distributions), how may one predict revenues from offering a particular assortment of choices? An outcome of our investigation is a non-parametric approach in which the data automatically selects the 'right' choice model for revenue predictions. The approach is practical. Using a data set consisting of automobile sales transaction data from a major US automaker, our method demonstrates a 20% improvement in prediction accuracy over state-of-the art benchmark models, which can result in a 10% increase in revenues from optimizing the offer set. We also address a number of theoretical issues, among them a qualitative examination of the choice models implicitly learned by the approach. We believe that this paper takes a step towards 'automating' the crucial task of choice model selection.



Bayesian Nonparametrics


Bayesian Nonparametrics
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Author : J.K. Ghosh
language : en
Publisher: Springer Science & Business Media
Release Date : 2006-05-11

Bayesian Nonparametrics written by J.K. Ghosh and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006-05-11 with Mathematics categories.


This book is the first systematic treatment of Bayesian nonparametric methods and the theory behind them. It will also appeal to statisticians in general. The book is primarily aimed at graduate students and can be used as the text for a graduate course in Bayesian non-parametrics.



Regression And Time Series Model Selection


Regression And Time Series Model Selection
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Author : Allan D. R. McQuarrie
language : en
Publisher: World Scientific
Release Date : 1998

Regression And Time Series Model Selection written by Allan D. R. McQuarrie and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 1998 with Mathematics categories.


This important book describes procedures for selecting a model from a large set of competing statistical models. It includes model selection techniques for univariate and multivariate regression models, univariate and multivariate autoregressive models, nonparametric (including wavelets) and semiparametric regression models, and quasi-likelihood and robust regression models. Information-based model selection criteria are discussed, and small sample and asymptotic properties are presented. The book also provides examples and large scale simulation studies comparing the performances of information-based model selection criteria, bootstrapping, and cross-validation selection methods over a wide range of models.