DSpace DSpace

University of Minnesota Digital Conservancy >
University of Minnesota - Twin Cities >
School of Statistics >
Dr. Charles Geyer >

Please use this identifier to cite or link to this item: http://hdl.handle.net/11299/135870

Title: Aster Models with Random Effects via Penalized Likelihood
Authors: Geyer, Charles J.
Ridley, Caroline E.
Latta, Robert G.
Etterson, Julie R.
Shaw, Ruth G.
Issue Date: 9-Oct-2012
Series/Report no.: Technical Report
692
Abstract: This technical report works out details of approximate maximum likelihood estimation for aster models with random effects. Fixed and random effects are estimated by penalized log likelihood. Variance components are estimated by integrating out the random effects in the Laplace approximation of the complete data likelihood following Breslow and Clayton (1993), which can be done analytically, and maximizing the resulting approximate missing data likelihood. A further approximation treats the second derivative matrix of the cumulant function of the exponential family where it appears in the approximate missing data log likelihood as a constant (not a function of parameters). Then first and second derivatives of the approximate missing data log likelihood can be done analytically. Minus the second derivative matrix of the approximate missing data log likelihood is treated as approximate Fisher information and used to estimate standard errors.
URI: http://purl.umn.edu/135870
Appears in Collections:Dr. Charles Geyer

Files in This Item:

File Description SizeFormat
tr692.pdfTechnical report433.34 kBPDFView/Open
tr692.RnwSweave source for the technical report119.32 kBTextView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.