Journal ArticleDOI
Precision, Complexity and Bayesian Model Determination
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In this article, a new criterion for model determination is proposed and an explicit decision theoretic approach to model selection is employed to derive a Bayes decision rule, and the operational characteristics of the criterion are discussed and consistency is shown.Abstract:
SUMMARY In this paper a new criterion for model determination is proposed. An explicit decision theoretic approach to model selection is employed to derive a Bayes decision rule. The operational characteristics of the criterion are discussed and consistency is shown.read more
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Journal ArticleDOI
Model uncertainty, data mining and statistical inference
TL;DR: The effects of model uncertainty, such as too narrow prediction intervals, and the non-trivial biases in parameter estimates which can follow data-based modelling are reviewed.
BookDOI
Decision theory : principles and approaches
TL;DR: A guided tour of decision theory can be found in this paper, where the authors present a set of decision-theoretic approaches to sample size, including the standard gamble, the "standard gamble of money", and the axioms of probabilities.
Journal ArticleDOI
Asymptotic MAP criteria for model selection
TL;DR: This paper derives maximum a posteriori (MAP) rules for several different families of competing models and obtain forms that are similar to AIC and naive MDL, but for some families, however, it is found that the derived penalties are different.
Journal ArticleDOI
Schwarz, Wallace, and Rissanen : Intertwining themes in theories of model selection
TL;DR: In this paper, a survey of the contributions of Schwarz, Wallace, Rissanen, and their coworkers attempts to build bridges between the various viewpoints, illuminating connections which may have previously gone unnoticed and clarifying misconceptions which seem to have propagated in the applied literature.
Book
Principles of Uncertainty
TL;DR: Probability Avoiding being a sure loser Disjoint events Events not necessarily disjoint Random variables, also known as uncertain quantities Finite number of values Other properties of expectation Coherence implies not a sure winner Expectations and limits Conditional Probability and Bayes Theorem Conditional probability The Birthday Problem Simpson's Paradox Bayes theorem Independence of events The Monty Hall problem Gambler's Ruin problem Iterated Expectation and Independence The binomial and multinomial distributions Sampling without replacement Variance and covariance A short introduction to multivariate thinking Tchebychev's
References
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Journal ArticleDOI
A new look at the statistical model identification
TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Journal ArticleDOI
Estimating the Dimension of a Model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Estimating the dimension of a model
TL;DR: In this paper, the problem of selecting one of a number of models of different dimensions is treated by finding its Bayes solution, and evaluating the leading terms of its asymptotic expansion.
Journal ArticleDOI