Accession Number:

ADA149873

Title:

Smoothing Estimation of Stochastic Processes: Change of Initial Condition Formulas,

Descriptive Note:

Corporate Author:

WISCONSIN UNIV-MADISON MATHEMATICS RESEARCH CENTER

Personal Author(s):

Report Date:

1984-01-01

Pagination or Media Count:

5.0

Abstract:

By posing the change of initial condition CIC problem in the theory of smoothing in linear estimation in a setting stripped of all inessentials, simple, insightful derivations of most CIC formulas and a new likelihood formula are provided. Specifically, the CIC or partitioning problem is one of low rank perturbation to a covariance kernel and the formulas are simple consequences of inversion formulas for fixed rank modification of a positive definite kernel or matrix. The present derivation basically handles the discrete, continuous-discrete, and continuous cases at once previous derivations had treated the discrete and continuous separately. The continuous- discrete results are new. Originator-supplied key words include Linear estimation, Smoothing, Filtering, Covariance kernel, Hilbert space.

Subject Categories:

  • Statistics and Probability

Distribution Statement:

APPROVED FOR PUBLIC RELEASE