DocumentCode :
1802868
Title :
Empirical Evaluation of Data-Based Density Estimation
Author :
Chen, E. Jack ; Kelton, W. David
Author_Institution :
BASF Corp., Rockaway, NJ
fYear :
2006
fDate :
3-6 Dec. 2006
Firstpage :
333
Lastpage :
341
Abstract :
This paper discusses implementation of a sequential procedure to estimate the steady-state density of a stochastic process. The procedure computes sample densities at certain points and uses Lagrange interpolation to estimate the density f(x). Even though the proposed sequential procedure is a heuristic, it does have strong basis. Our empirical results show that the procedure gives density estimates that satisfy a pre-specified precision requirement. An experimental performance evaluation demonstrates the validity of using the procedure to estimate densities
Keywords :
interpolation; stochastic processes; Lagrange interpolation; data-based density estimation; sequential procedure; stochastic process; Analytical models; Density functional theory; Histograms; Kernel; Lifting equipment; Probability density function; Random variables; Smoothing methods; Steady-state; Stochastic processes;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Simulation Conference, 2006. WSC 06. Proceedings of the Winter
Conference_Location :
Monterey, CA
Print_ISBN :
1-4244-0500-9
Electronic_ISBN :
1-4244-0501-7
Type :
conf
DOI :
10.1109/WSC.2006.323099
Filename :
4117623
Link To Document :
بازگشت