The deviance information criterion: 12 years on

By David J. Spiegelhalter, N. G. Best, Bradley P. Carlin, A. van der Linde. 2014

636 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/8388265d76a526bfec9ad3acaa19780ad9474cb8

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Citations in the corpus

KiDS-450 + 2dFLenS: Cosmological parameter constraints from weak gravitational lensing tomography and overlapping redshift-space galaxy clustering (2017, background): “Best & Carlin 2002, also see Liddle 2007; Trotta 2008; Spiegelhalter et al. 2014; Joudaki et al. 2017a), given by DIC ≡ χ2eff (θ̂ ) + 2pD. (19) The first term of the DIC is the best-fit effective χ2eff (θ̂ ) = −2 lnLmax, where θ̂ is the vector of varied parameters at the maximum likelihoodLmax of…”
KiDS-450: testing extensions to the standard cosmological model (2016, methodology): “…Joudaki et al. (2017) in using the DIC (Spiegelhalter, Best & Carlin 2002, also see Kunz, Trotta & Parkinson 2006; Liddle 2007; Trotta 2008, and Spiegelhalter et al. 2014), given by the sum of two terms: DIC ≡ χ2eff (θ̂) + 2pD. (1) Here, the first term consists of the best-fitting effective…”
Estimation of a non-stationary model for annual precipitation in southern Norway using replicates of the spatial field (2014, methodology): “DIC has been criticised, but is also frequently used (see Spiegelhalter et al. (2014) for a summary).”
CFHTLenS revisited: assessing concordance with Planck including astrophysical systematics (2016, methodology): “…performance of two distinct models, it is valuable to compute the DIC (Spiegelhalter et al. 2002, also see Kunz, Trotta & Parkinson 2006; Liddle 2007; Trotta 2008; Spiegelhalter et al. 2014), obtained from the Kullback–Leibler divergence or relative information entropy (Kullback & Leibler 1951).”
Programming With Models: Writing Statistical Algorithms for General Model Structures With NIMBLE (2015, methodology): “…et al., 1992; Stern and Cressie, 2000), calibrated posterior predictive p-values (Hjort et al., 2006) or alternatives to DIC such as WAIC (Watanabe, 2010; Spiegelhalter et al., 2014); (vi) “likelihood free” or “plug-and-play” methods such as synthetic likelihood (Wood, 2010), approximate Bayesian…”