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searching for Marginal likelihood 8 found (32 total)

Generalized additive model (5,716 words) [view diff] case mismatch in snippet view article find links to article

information criterion (AIC). Finally we may choose to maximize the Marginal Likelihood (REML) obtained by integrating the model coefficients, β {\displaystyle

Siddhartha Chib (2,033 words) [view diff] exact match in snippet view article find links to article

calculating the marginal likelihood for Bayesian model comparisons. The method relies on an identity that expresses the marginal likelihood as the product

Relevance vector machine (425 words) [view diff] case mismatch in snippet view article find links to article

Research. 1: 211–244. Tipping, Michael; Faul, Anita (2003). "Fast Marginal Likelihood Maximisation for Sparse Bayesian Models". Proceedings of the Ninth

Kernel methods for vector output (4,220 words) [view diff] exact match in snippet view article find links to article

solution for the posterior distribution or for the marginal likelihood. However, the marginal likelihood can be approximated under a Laplace, variational

Smoothing spline (2,314 words) [view diff] exact match in snippet view article find links to article

often estimated by generalized cross-validation, or by restricted marginal likelihood (REML)[citation needed] which exploits the link between spline smoothing

Comparison of Gaussian process software (1,681 words) [view diff] exact match in snippet view article find links to article

"Manually", the software provides an interface for computing the marginal likelihood and its gradient w.r.t. hyperparameters, which can be feed into an

Dynamic causal modeling (3,917 words) [view diff] exact match in snippet view article find links to article

Laplace assumption. This provides two useful quantities: the log marginal likelihood or model evidence ln ⁡ p ( y | m ) {\displaystyle \ln {p(y|m)}} is

German tank problem (6,376 words) [view diff] exact match in snippet view article find links to article

more than this, potentially many more, but cannot be fewer. The marginal likelihood (i.e. marginalized over all models) is infinite, being a tail of