10/24/2014

Post date: Oct 26, 2014 5:21:52 PM

"An overview of composite likelihood methods" (Slides)

Chiung-Yu Huang, Division of Biostatistics and Bioinformatics, SKCCC, Johns Hopkins University

The composite likelihood method developed by Lindsay (1988) and Arnold and Strauss (1988), whose idea dates back to Besag (1974), is based on a pseudo-likelihood constructed by compounding low-dimensional marginal or conditional densities. This approach is especially useful for large dimensional data where a fully specified model may not be available or difficult to evaluate. As recently highlighted in a special issue of Statistica Sinica in January 2011, the composite likelihood method has drawn a good deal of attention and has been widely applied to many important areas of research, including longitudinal data analysis, spatial analysis, and statistical genetics, among others. In this talk, I will give an overview of the composite likelihood method and present a survey of its applications.