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Statistical Distances as Loss Functions in Assessing Model Adequacy

Bruce G. Lindsay

in The Nature of Scientific Evidence: Statistical, Philosophical, and Empirical Considerations

Published in print:
2004
Published Online:
February 2013
ISBN:
9780226789552
eISBN:
9780226789583
Item type:
chapter
Publisher:
University of Chicago Press
DOI:
10.7208/chicago/9780226789583.003.0014
Subject:
Biology, Ecology

This chapter takes on the problem of model adequacy and makes an argument for reformulating the way model-based statistical inference is carried out. In the new formulation, it does not treat the ... More


Robust Prediction Under Model Misspecification

Raymond L. Chambers and Robert G. Clark

in An Introduction to Model-Based Survey Sampling with Applications

Published in print:
2012
Published Online:
May 2012
ISBN:
9780198566625
eISBN:
9780191738449
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198566625.003.0008
Subject:
Mathematics, Probability / Statistics

Robust prediction under model misspecification focuses on the important topic of how to ensure unbiased prediction even when the assumed population model is not precisely specified. The general role ... More


Using Transformations in Sample Survey Inference

Raymond L. Chambers and Robert G. Clark

in An Introduction to Model-Based Survey Sampling with Applications

Published in print:
2012
Published Online:
May 2012
ISBN:
9780198566625
eISBN:
9780191738449
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780198566625.003.0017
Subject:
Mathematics, Probability / Statistics

Using transformations in sample survey inference is the final chapter of this book and describes the extension of the empirical best prediction approach to the situation where the population values ... More


Learning and Model Validation: An Example *

In‐Koo Cho and Kenneth Kasa

in Macroeconomics at the Service of Public Policy

Published in print:
2013
Published Online:
May 2013
ISBN:
9780199666126
eISBN:
9780191749278
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199666126.003.0006
Subject:
Economics and Finance, Macro- and Monetary Economics

This chapter studies adaptive learning with multiple models. An agent is aware of potential model misspecification, and tries to detect it, in realtime, using an econometric specification test. If ... More


Analyzing and Comparing the Geometry of Individual Fitness Surfaces

Stephen F. Chenoweth, John Hunt, and Howard D. Rundle

in The Adaptive Landscape in Evolutionary Biology

Published in print:
2013
Published Online:
December 2013
ISBN:
9780199595372
eISBN:
9780191774799
Item type:
chapter
Publisher:
Oxford University Press
DOI:
10.1093/acprof:oso/9780199595372.003.0009
Subject:
Biology, Evolutionary Biology / Genetics

For almost 30 years, Lande and Arnold's approximation of individual fitness surfaces through multiple regression has provided a common framework for comparing the strength and form of phenotypic ... More


Introduction and Problem Formulation

Masashi Sugiyama and Motoaki Kawanabe

in Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation

Published in print:
2012
Published Online:
September 2013
ISBN:
9780262017091
eISBN:
9780262301220
Item type:
chapter
Publisher:
The MIT Press
DOI:
10.7551/mitpress/9780262017091.003.0001
Subject:
Computer Science, Machine Learning

This chapter provides an introduction to covariate shift adaptation toward machine learning in a non-stationary environment. It begins by discussing cover machine learning under covariate shift. It ... More


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