DocumentCode
1812881
Title
Estimating the variance in case of undermodeling using bootstrap
Author
Tjärnström, Fredrik ; Ljung, Lennart
Author_Institution
Dept. of Electr. Eng., Linkoping Univ., Sweden
Volume
3
fYear
1999
fDate
1999
Firstpage
2394
Abstract
Simulation based methods have gained interest in the signal processing community. In this article we propose an algorithm to estimate the probability density function of some statistic associated with an identified model in the case of undermodeling. With this algorithm, we are thus able to estimate the variance error of any statistic associated with the model. We also give a simulation example, which shows that the estimates are in very good agreement with Monte Carlo simulations
Keywords
Monte Carlo methods; covariance matrices; estimation theory; identification; probability; signal processing; bootstrap; probability density function; undermodeling; variance error; variance estimation; Accuracy; Automatic control; Computer aided software engineering; Error analysis; Maximum likelihood estimation; Probability density function; Signal processing algorithms; Statistics; Stochastic processes; Time measurement;
fLanguage
English
Publisher
ieee
Conference_Titel
Decision and Control, 1999. Proceedings of the 38th IEEE Conference on
Conference_Location
Phoenix, AZ
ISSN
0191-2216
Print_ISBN
0-7803-5250-5
Type
conf
DOI
10.1109/CDC.1999.831283
Filename
831283
Link To Document