𝔖 Bobbio Scriptorium
✦   LIBER   ✦

Filtering via estimating functions

✍ Scribed by M.E. Thompson; A. Thavaneswaran


Book ID
104350237
Publisher
Elsevier Science
Year
1999
Tongue
English
Weight
305 KB
Volume
12
Category
Article
ISSN
0893-9659

No coin nor oath required. For personal study only.

✦ Synopsis


A result of Godambe [1] on optimal combination of estimating functions for discrete time stochastic processes is extended to discrete time state space models and to continuous time counting process models. The extensions so obtained may be applicable in a wider context than the standard notions based upon the conditional mean. It is shown that a number of results in the literature are special cases. The theory is applied to obtain recursive estimates for continuous time counting processes. Optimal linear combination of estimating functions can shed light on the form of recursion satisfied by the usual filter, namely conditional expectation of the unobserved underlying process given the observation history.


πŸ“œ SIMILAR VOLUMES


Interval estimation via tail functions
✍ Borek Puza; Terence O'Neill πŸ“‚ Article πŸ“… 2006 πŸ› John Wiley and Sons 🌐 French βš– 631 KB
Filtering non-periodic functions
✍ Sidi Mahmoud Ould Kaber πŸ“‚ Article πŸ“… 1994 πŸ› Elsevier Science 🌐 English βš– 414 KB

We consider a non-periodic function u with Legendre expansion Eke, 0 ~L k. The best approximation of u, in the L 2 sense, by N N-degree polynomials is the truncated series ~rNu = E~. 0 ~kLk. When the function u is discontinuous, the polynomial approximation rrNu is oscillatory. We present a filter t