Pairwise likelihood approach to grouped continuous model and its extension

By A. R. Leon. 2005

57 citations recorded by the source corpus.

Subfields: Environmental Engineering, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/3bac2d71268c1c12d536423ba3dc14b8c33da1e0

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Environmental Engineering

In Statistics and Probability

Citations in the corpus

Fitting Vast Dimensional Time-Varying Covariance Models (2020, methodology): “…function using marginal univariate likelihoods (this type of marginal analysis has appeared before outside the time-series literature, e.g., Besag (1974) in spatial processes, LeCessie and van Houwelingen (1994) and Kuk and Nott (2000) for correlated binary data, and deLeon (2005) on grouped data).”
A note on pseudolikelihood constructed from marginal densities (2004, methodology): “A more general version of the dichotomized normal, in which a latent multivariate normal random vector is categorized into several classes, is treated by the method of pairwise likelihood in deLeon (2003), extending a method proposed by Anderson and Pemberton (1985).”
A comparison of the maximum simulated likelihood and composite marginal likelihood estimation approaches in the context of the multivariate ordered-response model (2010, methodology): “Almost all earlier research efforts employing the CML technique have used the pairwise approach, including Apanasovich et al. (2008), Bellio and Varin (2005), de Leon (2005), Varin and Vidoni (2009), Varin et al. (2005), and Engle et al. (2007).”
General mixed‐data model: Extension of general location and grouped continuous models (2007, background): “As recently shown by de Leon (2005) and Renard, Molenberghs & Geys (2009, there is little to moderate loss in efficiency for MPL estimates; in addition, generally few convergence difficulties are encountered in its implementation.”