𝔖 Bobbio Scriptorium
✦   LIBER   ✦

An algorithm for estimating parameters of state-space models

✍ Scribed by Lilian Shiao-Yen Wu; Jeffrey S. Pai; J.R.M. Hosking


Publisher
Elsevier Science
Year
1996
Tongue
English
Weight
449 KB
Volume
28
Category
Article
ISSN
0167-7152

No coin nor oath required. For personal study only.


πŸ“œ SIMILAR VOLUMES


The semi-relaxed algorithm for estimatin
✍ Li Deng πŸ“‚ Article πŸ“… 1991 πŸ› Elsevier Science 🌐 English βš– 489 KB

For hidden Markov model (HMM) based speech recognition where the basic speech unit is smaller than the recognizer's output unit, the standard full Baum-Welch re-estimation procedure for the HMM training is very costly in computation. This is hecause it requires evaluation of the HMM output densities

State-space stochastic volatility models
✍ Capobianco, Enrico πŸ“‚ Article πŸ“… 1996 πŸ› John Wiley and Sons 🌐 English βš– 904 KB

Stochastic volatility models (SVMs) represent an important framework for the analysis of financial time series data, together with ARCH-type models; but unlike the latter, the former, at least from the statistical point of view, cannot rely on the possibility of obtaining exact inference, in particu

An efficient adaptive frequency sampling
✍ Robert Lehmensiek; Petrie Meyer πŸ“‚ Article πŸ“… 2000 πŸ› John Wiley and Sons 🌐 English βš– 161 KB πŸ‘ 2 views

A fast and efficient adapti¨e sampling algorithm is presented. This algorithm is applied to the aggressi¨e space mapping technique to minimize the number and to automate the selection of frequency sample points of the fine model, thus impro¨ing the efficiency of space mapping. The new technique is a

Filtering and smoothing algorithms for s
✍ R. Kohn; C.F. Ansley πŸ“‚ Article πŸ“… 1989 πŸ› Elsevier Science 🌐 English βš– 790 KB

The paper reviews and generalizes recent filtering and smoothing algorithms for observations generated by a state model. In particular the paper discusses the modified Kalman filter derived by Ansley and Kohn (1985) and Kohn and Ansley (1986) to deal with state space models having partially diffuse