Estimating Functions with Prior Knowledge, (EFPK) for diffusions

Estimating Functions with Prior Knowledge, (EFPK) for diffusions

Abstract	In this paper a method is formulated in an estimating function setting for parameter estimation, which allows the use of prior information. The main idea is to use prior knowledge of the parameters, either specified as moments restrictions or as a distribution, and use it in the construction of an estimating function. It may be useful when the full Bayesian analysis is difficult to carry out for computational reasons. This is almost always the case for diffusions, which is the focus of this paper, though the method applies in other settings.
Keywords	Small sample size, Estimating Functions, Diffusion Process, Cox Ingersoll & Ross (CIR) Process, Ornstein-Uhlenbeck Process
Type	Technical report
Year	2003
Publisher	Informatics and Mathematical Modelling, Technical University of Denmark, DTU
Address	Richard Petersens Plads, Building 321, DK-2800 Kgs. Lyngby
Series	IMM-Technical report-2003-28
Electronic version(s)	[pdf]
BibTeX data	[bibtex]
IMM Group(s)	Mathematical Statistics