•   •   •   •

Download the Paper (189 K, PDF file) - January 1, 2006 Tell a colleague about it. Printing Tips: Select 'print as image' in the Acrobat print dialog if you have trouble printing.

ABSTRACT:
For models used to describe multi-dimensional marked point processes with covariates, the high number of parameters typically involved and the high dimensionality of the process can make model evaluation, construction, and estimation using maximum likelihood quite difficult. Conditions are explored here under which parameters governing one set of coordinates or covariates affecting a multi-dimensional marked point process may be estimated separately. The resulting estimates are, under the given conditions, similar to maximum likelihood estimates.

SUGGESTED CITATION:
Frederic P. Schoenberg, "A Note on the Separability of Multidimensional Point Processes with Covariates" (January 1, 2006). Department of Statistics, UCLA. Department of Statistics Papers. Paper 2006010108.
http://repositories.cdlib.org/uclastat/papers/2006010108