Present Position and Potential Developments: Some Personal Views: Statistical Theory: The Prequential Approach

Dawid, A. P.

doi:10.2307/2981683

Cited by 888 publications

(372 citation statements)

References 18 publications

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“…compare MDL and MML from a predictive point of view. The predictive interpretation of MDL has close analogies with Dawid's prequential principle (Dawid 1984; and a version of cross-validation called forward validation (Rissanen 1989, Section 3.3). In some cases, it is not necessary to pick a specific model order; it may be better, in fact, to employ all the models in a weighted fashion (Wasserman, 2000;Hoeting et al, 1999;Chickering & Heckerman, 2000), as Singer & Feder (1999) illustrate for linear least-squares prediction problems.…”

Section: Resultsmentioning

confidence: 98%

Schwarz, Wallace, and Rissanen: Intertwining Themes in Theories of Model Selection

Lanterman¹

2001

International Statistical Review / Revue Internationale de Stat

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Investigators interested in model order estimation have tended to divide themselves into widely separated camps; this 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. Our tour begins with Schwarz's approximation of Bayesian integrals via Laplace's method. We then introduce the concepts underlying Rissanen's minimum description length principle via a Bayesian scenario with a known prior; this provides the groundwork for understanding his more complex non-Bayesian MDL which employs a "universal" encoding of the integers. Rissanen's method of parameter truncation is contrasted with that employed in various versions of Wallace's minimum message length criteria. Rissanen's more recent notion of stochastic complexity is outlined in terms of Bernardo's information-theoretic derivation of the Jeffreys prior.

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Section: Resultsmentioning

confidence: 98%

Schwarz, Wallace, and Rissanen: Intertwining Themes in Theories of Model Selection

Lanterman¹

2001

International Statistical Review / Revue Internationale de Stat

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“…Given the probabilities generated by each individual predictor, P(Z t = 1|X it ) for i = 1, 2, ..., I, all of which may be perfectly calibrated in the sense of Dawid (1984) 4 , the linearly combined forecast can be constructed by taking the linear pool, that is,…”

Section: Relationship With Extant Methodsmentioning

confidence: 99%

A non-linear forecast combination procedure for binary outcomes

Lahiri

Liu²

2016

Studies in Nonlinear Dynamics &Amp; Econometrics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. We develop a non-linear forecast combination rule based on copulas that incorporate the dynamic interaction between individual predictors. This approach is optimal in the sense that the resulting combined forecast produces the highest discriminatory power as measured by the receiver operating characteristic (ROC) curve. Under additional assumptions, this rule is shown to be equivalent to the quintessential linear combination scheme. To illustrate its usefulness, we apply this methodology to optimally aggregate two currently used leading indicators-the ISM new order diffusion index and the yield curve spread-to predict economic recessions in the United States. We also examine the sources of forecasting gains using a counterfactual experimental set up. Terms of use: Documents in

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“…Having witnessed a finite sequence σ of bits, we are to make a probability forecast, based on σ only, of what bit comes next; then this bit is revealed, and the procedure is repeated. Dawid (1984) names it the prequential approach, for sequential prediction in a probabilistic fashion.…”

Section: Setting the Stagementioning

confidence: 99%

Solomonoff Prediction and Occam’s Razor

Sterkenburg¹

2016

Philos. of Sci.

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Abstract. Algorithmic information theory gives an idealized notion of compressibility, that is often presented as an objective measure of simplicity. It is suggested at times that Solomonoff prediction, or algorithmic information theory in a predictive setting, can deliver an argument to justify Occam's razor. This paper explicates the relevant argument, and, by converting it into a Bayesian framework, reveals why it has no such justificatory force. The supposed simplicity concept is better perceived as a specific inductive assumption, the assumption of effectiveness. It is this assumption that is the characterizing element of Solomonoff prediction, and wherein its philosophical interest lies.

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Present Position and Potential Developments: Some Personal Views: Statistical Theory: The Prequential Approach

Cited by 888 publications

References 18 publications

Schwarz, Wallace, and Rissanen: Intertwining Themes in Theories of Model Selection

Schwarz, Wallace, and Rissanen: Intertwining Themes in Theories of Model Selection

A non-linear forecast combination procedure for binary outcomes

Solomonoff Prediction and Occam’s Razor

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