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Deviance information criterion
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#	Item
1	Evidence Estimation for Bayesian Partially Observed MRFs Yutian Chen Department of Computer Science University of California, Irvine Irvine, CA 92697 Add to Reading List Source URL: www.ics.uci.edu Language: English - Date: 2013-02-14 03:02:58 Normal distribution Expectation–maximization algorithm Variational Bayesian methods Bayesian network Markov chain Monte Carlo Maximum likelihood Deviance information criterion Pierre-Simon Laplace Markov random field Statistics Bayesian statistics Marginal likelihood
2	PDF Document Add to Reading List Source URL: www.taos-telecommunity.org Language: English - Date: 2008-03-04 16:18:06 Statistical classification Naive Bayes classifier Machine learning Influence diagram Deviance information criterion Gibbs sampling Expectation–maximization algorithm Bayesian information criterion Book:Machine Learning - The Complete Guide Statistics Bayesian statistics Bayesian network
3	A primer for data assimilation with ecological models using Markov Chain Monte Carlo (MCMC) J. M. Zobitz, A. R. Desai, D. J. P. Moore & M. A. Chadwick Add to Reading List Source URL: ccr.meteor.wisc.edu Language: English - Date: 2012-08-14 09:49:09 Monte Carlo methods Model selection Computational statistics Data assimilation Ensemble Kalman filter Deviance information criterion Least squares Ecosystem model Parameter Statistics Bayesian statistics Estimation theory
4	Joint Statistics Seminar The Hong Kong University of Science and Technology Predictive Likelihood for Bayesian Model Selection and Averaging by Add to Reading List Source URL: www.bm.ust.hk Language: English - Date: 2008-09-10 03:26:26 Bayesian statistics Model selection Bayesian inference Bayes factor Likelihood function Deviance information criterion Statistics Estimation theory Statistical theory
5	Stock assessment of short-lived invertebrates using hierarchical Bayesian models Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-16 21:22:25 Stock assessment Hierarchical Bayes model Prior probability Bayesian inference Hyperparameter Maximum sustainable yield Bycatch Hyperprior Statistics Bayesian statistics Deviance information criterion
6	How reliable is my reliability model? Add to Reading List Source URL: www.mssanz.org.au Language: English - Date: 2013-01-16 21:21:38 Survival analysis Bayesian inference Model selection Statistical models Weibull distribution Deviance information criterion Mixture model Bayesian information criterion Reliability engineering Statistics Probability and statistics Bayesian statistics
7	Generalized Linear Models Contents 1 Introducing GLMs 1.1 Examples of GLMsInference with GLMsglm in R . . . . . . . . . . . . . Add to Reading List Source URL: people.bath.ac.uk Language: English - Date: 2010-12-21 12:26:03 Deviance Akaike information criterion Least squares Errors and residuals in statistics Statistics Regression analysis Generalized linear model
8	JIMAR, PFRP ANNUAL PROGRESS REPORT: FYApril 2003 P.I. Name: Benjamin Bolker Project Proposal Title: Development of a hierarchical model to estimate sea turtle rookery contributions to mixed stocks in foraging ha Add to Reading List Source URL: www.soest.hawaii.edu Language: English - Date: 2006-08-22 14:56:28 Deviance information criterion Hierarchical Bayes model Ecology Rookery Statistical power Akaike information criterion Bayes factor Statistics Bayesian statistics Model selection
9	Logistic regression (with R) Christopher Manning 4 November Add to Reading List Source URL: www-nlp.stanford.edu Language: English - Date: 2007-11-14 02:47:21 Model selection Actuarial science Deviance Hypothesis testing Logistic regression Logit Akaike information criterion Logistic function Degrees of freedom Statistics Categorical data Regression analysis
10	J. R. Statist. Soc. B, Part 2, pp. 319–392 Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations Add to Reading List Source URL: www.math.ntnu.no Language: English - Date: 2011-12-21 15:18:36 Estimation theory Markov models Probability theory Variational Bayesian methods Mixture model Normal distribution Marginal likelihood Deviance information criterion Gaussian process Statistics Probability and statistics Bayesian statistics