Deviance Information Criterion
In der Statistik ist das Abweichungsinformationskriterium (engl. deviance information criterion, DIC) ein Maß (Kriterium) für den Vorhersagefehler eines Modells.
Diese Maßzahl ist ein Informationskriterium und gehört in das Umfeld der Bayesianischen Methode für Modellvergleiche. Je kleiner das DIC, desto besser ist die Modellpassung. Das DIC kann als Bayesianische Entsprechung des AIC betrachtet werden.
Bei der Bewertung zweier Modelle mit unterschiedlichem DIC gilt sehr grob formuliert: Bei Unterschieden größer als 10 ist das Modell mit dem höheren DIC definitiv schlechter, Unterschiede zwischen 5 und 10 sind substantiell, bei Unterschieden kleiner als 5 und deutlich unterschiedlichen Modellformulierungen kann es nötig sein, beide Modelle in Betracht zu ziehen.

Dies ist ein Auszug aus dem Artikel Deviance Information Criterion der freien Enzyklopädie Wikipedia. In der Wikipedia ist eine Liste der Autoren verfügbar.
Auf de.wikipedia.org wurde der Artikel Deviance Information Criterion in den letzten 30 Tagen 92-mal aufgerufen. (Stand: 03.07.2014)
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Deviance Information Criterion – Wikipedia
In der Statistik ist das Abweichungsinformationskriterium (engl. Deviance Information Criterion, DIC) ein Maß (Kriterium) für den Vorhersagefehler eines Modells.
de.wikipedia.org/wiki/Deviance_Information_Criterion
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Deviance information criterion - Wikipedia, the free encyclopedia
The Deviance Information Criterion (DIC) is a hierarchical modeling generalization of the AIC (Akaike information criterion) and BIC (Bayesian information ...
en.wikipedia.org/wiki/Deviance_information_criterion
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DIC: Deviance Information Criterion
site. OpenBUGS site. DIC: Deviance Information. Criterion. DIC (Deviance Information Criterion) is a Bayesian method for model comparison that WinBUGS can ...
users.jyu.fi/~hemipu/itms/DIC%20web%20site%20from%20BUGS%20project.pdf
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Model Fit and Bayesian Inference
The sum of both the mean model-level deviance and the model complexity (pD or pV) is the Deviance Information Criterion (DIC), a model fit statistic that is also ...
www.bayesian-inference.com/modelfit
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Deviance Information Criterion for Comparing Stochastic Volatility ...
the Deviance Information Criterion (DIC), a Bayesian version or generalization of the well-known Akaike information criterion. (AIC) (Akaike 1973), related also to ...
www.mysmu.edu/faculty/yujun/research/yujbes.pdf
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Some DIC slides - Voteview.com
12 Feb 2006 ... Spiegelhalter et al (2002) proposed a Bayesian model comparison criterion based on this principle: Deviance Information Criterion, DIC ...
voteview.com/DIC-slides.pdf
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Robust Deviance Information Criterion for Latent Variable Models
ical underpinnings of the Deviance Information Criterion (DIC), a widely used information criterion for Bayesian model comparison, although it facilitates ...
apps.olin.wustl.edu/conf/SBIES/Files/pdf/2013/82.pdf
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Deviance Information Criteria for Missing Data Models - Bayesian ...
The Deviance Information Criterion (DIC) introduced by Spiegelhalter et al. (2002) for model assessment and model comparison is directly inspired by linear.
ba.stat.cmu.edu/journal/2006/vol01/issue04/celeux.pdf
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A Caution about using Deviance Information Criterion ... - CEProfs
Geedipally, Lord and Dhavala. 1. A Caution about using Deviance Information Criterion While Modeling. Traffic Crashes. Technical Communication. Srinivas ...
ceprofs.civil.tamu.edu/dlord/Papers/Geedipally_et_al_DIC_PGNB.pdf
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Deviance, DIC, AIC, cross-validation, etc « Statistical Modeling ...
Deviance, DIC, AIC, cross-validation, etc. Posted by Andrew on 22 June 2011, 9: 55 am. The Deviance Information Criterion (or DIC) is an idea of Brad Carlin and ...
andrewgelman.com/2011/06/22/deviance_dic_ai/
Suchergebnisse für "Deviance Information Criterion"
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Deviance Information Criterion in der Wissenschaft
[PDF]this paper
Institute of Statistics, University of Bremen, ... Email: avdl@math.uni-bremen.de ... The Deviance Information Criterion (DIC) was introduced by Spiegelhalter et al ...
Bayesian measures of model complexity and fit (pages 583–639)
23 Oct 2002 ... Bayesian model comparison;; Decision theory;; Deviance Information Criterion;; Effective number of parameters;; Hierarchical models; ...
[PDF]Robust Deviance Information Criterion for Latent Variable Models
Robust Deviance Information Criterion for Latent. Variable Models. ∗. Yong Li. Renmin University of China. Tao Zeng. Singapore Management University.
On Identifying the Optimal Number of Population Clusters via the ...
28 Jun 2011 ... Editor: Henry Harpending, University of Utah, United States of America ... The Deviance Information Criterion (DIC) is a recently proposed ...
[PDF]A Caution about using Deviance Information Criterion ... - CEProfs
Texas A&M University System ... performance criterion, Bayesian Information Criterion (BIC), among others need to be considered in addition ... Keywords: Deviance Information Criterion, Poisson-gamma, Negative Binomial, Traffic. Crashes.
[PDF]On Variational Bayes Estimation and Variational Bayes Information ...
a variational Bayes approximation to the Deviance Information Criterion, we ... School of Mathematics and Statistics, University of Sydney, Sydney 2006, ...
[PDF]Deviance Information Criteria for Missing Data Models - Ceremade
3CREST and CEREMADE, Uni. Paris Dauphine, and 4University of Glasgow. Abstract. The Deviance Information Criterion (DIC) introduced by Spiegel- halter et  ...
[PDF]Bayesian Model Selection - University of Missouri
University of York, UK ca505@york.ac.uk. 2007-03-13, Linköping .... The DIC (Deviance Information Criterion) is defined in anology with the AIC (Akaike's.
How to interpret strong break in slope of the Deviance Information ...
20 Jun 2013 ... How to interpret strong break in slope of the Deviance Information Criterion (DIC) with ... Gabor Borgulya · St George's, University of London.
[PDF]Deviance Information Criterion for Comparing Stochastic ... - Jstor
Deviance. Information Criterion for Comparing. Stochastic. Volatility Models. Andreas Berg. Department of Statistics, University of Auckland, Private Bag 92019, ...
Bücher zum Begriff Deviance Information Criterion
Klein aber fein!: Quantitative empirische Sozialforschung mit kleinen Fallzahlen (Forschung und Entwicklung in...
Klein aber fein!: Quantitative empirische Sozialforschung mit kleinen Fallzahlen (Forschung und Entwicklung in...
Peter Kriwy und Christiane Gross von VS Verlag für Sozialwissenschaften, 2008
Der Sammelband thematisiert die Arbeit mit kleinen Fallzahlen in der quantitativen empirischen Sozialforschung. Die Beitragsautoren stellen zunächst anwendungsorientiert methodische Grundlagen der Datenerhebung und -analyse kleiner Fallzahlen, z.B. Datenerhebung bei Spezialpopulationen und Regressionsdiagnostik vor. Neben der klassischen Methodik w...
Real World Ecology: Large-Scale and Long-Term Case Studies ...
Real World Ecology: Large-Scale and Long-Term Case Studies ...
ShiLi Miao, Susan Carstenn, Martha K. Nungesser, 2008
criteria are the Akaike Information Criterion (AIC, Akaike 1973), the Bayesian Information Criteria (BIC, Schwarz 1978), and the Deviance Information Criterion (DIC, Spiegelhalter et al. 2002). The goodness of fit component for all these make  ...
Regression: Modelle, Methoden und Anwendungen (Statistik und ihre Anwendungen)
Regression: Modelle, Methoden und Anwendungen (Statistik und ihre Anwendungen)
Ludwig Fahrmeir, Thomas Kneib und Stefan Lang von Springer, 2007
Diese Einführung beschreibt erstmals klassische Regressionsansätze und moderne nicht- und semiparametrische Methoden: integriert, einheitlich und anwendungsorientiert. Sie wendet sich an Studierende der Statistik im Wahl- und Hauptfach sowie an empirisch-statistisch und interdisziplinär arbeitende Wissenschaftler. Ebenso ist sie empfehlenswert für ...
Bayesian Disease Mapping: Hierarchical Modeling in Spatial ...
Bayesian Disease Mapping: Hierarchical Modeling in Spatial ...
Andrew B. Lawson, 2013
This is widely used for fixed effect models and is the basis of the Deviance Information Criterion discussed below. Another variant that is commonly used as a model choice criterion is the Bayesian information criterion (BIC). This is widely used ...
Demokratie als Leidenschaft: Planung, Entscheidung und Vollzug in der schweizerischen Demokratie (Festschrift...
Demokratie als Leidenschaft: Planung, Entscheidung und Vollzug in der schweizerischen Demokratie (Festschrift...
Adrian Vatter (Herausgeber), Fritz Sager (Herausgeber) und Frédéric Varone (Herausgeber) von Haupt Verlag, 2009
Der vorliegende Sammelband «Demokratie als Leidenschaft» bildet die Festschrift zum 65.Geburtstag und zur Emeritierung von Wolf Linder. Der erste Teil des Buches geht auf die Person Wolf Linder ein und fokussiert auf die facettenreichen Rollen des Begründers und erfolgreichen Leiters des Instituts für Politikwissenschaft an der Universität Bern. Di...
Deviance Information Criterion
Deviance Information Criterion
Frederic P. Miller, Agnes F. Vandome, McBrewster John, 2010
Please note that the content of this book primarily consists of articles available from Wikipedia or other free sources online.
Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
Kenneth P. Burnham von Springer, 2013
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains...
Information Criteria and Statistical Modeling
Information Criteria and Statistical Modeling
Sadanori Konishi, Genshiro Kitagawa, 2008
Chapter 9 discusses model selection and evaluation criteria within the Bayesian framework, in which we consider Schwarz's (1978) Bayesian information criterion , Akaike's (1980b) Bayesian information criterion (ABIC), a predictive ...
Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
Model Selection and Multimodel Inference: A Practical Information-Theoretic Approach
Kenneth P. Burnham und David R. Anderson von Springer, 2004
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains...
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Blog-Einträge zum Begriff
Deviance Information Criterion
Asymptotic Equivalence of Bayes Cross Validation and Widely ...
jmlr.org/papers/v11/watanabe10a.html
Understanding predictive information criteria for Bayesian models | StatsBlogs.com | All About Statistics
(This article was originally published at Statistical Modeling, Causal Inference, and Social Science, and syndicated at StatsBlogs. ) Jessy, Aki, and I write: We review the Akaike, deviance, and Watanabe-Akaike information criteria from a Bayesian perspective, where the goal is to estimate expected out-of-sample-prediction error using a bias-corrected adjustment of within-sample error.
www.statsblogs.com/2013/08/09/understanding-predictive-information-criteria-for-bayesian-models/
Deviance, DIC, AIC, cross-validation, etc « Statistical Modeling, Causal Inference, and Social Science Statistical Modeling, Causal Inference, and Social Science
andrewgelman.com/2011/06/22/deviance_dic_ai/
inference - What can we say about the likelihood function, besides using it in maximum likelihood estimation? - Cross Validated
stats.stackexchange.com/questions/63787/what-can-we-say-about-the-likelihood-function-besides-using-it-in-maximum-likel
AIM workshop on model choice | JAGS News
Next month I shall be attending a workshop at the American Institute of Mathematics on Singular learning theory: connecting algebraic geometry and model selection in statistics . The participants were invited to share their goals for the meeting. I can't show you the other contributions, but here is mine. My main interest is in statistical…
martynplummer.wordpress.com/2011/11/11/aim-workshop-on-model-choice/
On Marginal Likelihoods and Widely Applicable BIC ← The Spectator
blog.shakirm.com/2013/03/marginal-likelihood-wbic/
kim_tree 1.0 - Estimating Divergence Times on a Diffusion Time Scale from large SNP data sets
www.mybiosoftware.com/population-genetics/11594
"A Comparative Study of Bayesian Model Selection Criteria for Capture-R" by Ross M. Gosky and Sujit K. Ghosh
Capture-Recapture models estimate unknown population sizes. Eight standard closed population models exist, allowing for time, behavioral, and heterogeneity effects. Bayesian versions of these models are presented and use of Akaike's Information Criterion (AIC) and the Deviance Information Criterion (DIC) are explored as model selection tools, through simulation and real dataset analysis.
digitalcommons.wayne.edu/jmasm/vol8/iss1/6/
【3月14日】Robust Deviance Information Criterion for Latent Variable Models/经济学讲座 - 中国经济学教育科研网
Robust Deviance Information Criterion for Latent Variable 
www.cenet.org.cn/article.asp?articleid=69145
Phylogenetic Tools for Comparative Biology: New version of threshDIC
I just posted a new version of threshDIC for computing the Deviance Information Criterion from the object returned by ancThresh. The previous version (of threshDIC not ancThresh) just plain doesn't work.
blog.phytools.org/2012/12/new-version-of-threshdic.html
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