IDENTIFYING AN OBSERVABLE PROCESS WITH ONE OF SEVERAL SIMULATION MODELS VIA UMPI TEST

Nicholas A. Nechval, Konstantin N. Nechval, Edgars K. Vasermanis, Kristine Rozite

2004

Abstract

In this paper, for identifying an observable process with one of several simulation models, a uniformly most powerful invariant (UMPI) test is developed from the generalized maximum likelihood ratio (GMLR). This test can be considered as a result of a new approach to solving the Behrens-Fisher problem when covariance matrices of multivariate normal populations (compared with respect to their means) are different and unknown. The test is based on invariant statistic whose distribution, under the null hypothesis, does not depend on the unknown (nuisance) parameters.

References

  1. Alewell, C. and Manderscheid, B., 1998. Use of objective criteria for the assessment of biogeochemical ecosystem models. Ecol. Modelling, 105, 113-124.
  2. Banks, J. and Carson, J.S., 1984. Discrete-event System Simulation. NJ : Prentice-Hall, Englewood Cliffs.
  3. Bartelink, H.H., 1998. Radiation interception by forest trees: a simulation study on effects of stand density and foliage clustering on absorption and transmission. Ecol. Modelling, 105, 213-225.
  4. Freese, F., 1960. Testing accuracy. Forest Sci., 6, 139- 145.
  5. Jans-Hammermeister, D.C. and McGill, W.B., 1997. Evaluation of three simulation models used to describe plant residue decomposition in soil. Ecol. Modelling, 104, 1-13.
  6. Kleijnen, J.P.C., 1995. Verification and validation of simulation models. European Journal of Operational Research, 82, 145-162.
  7. Law, A.M. and W.D. Kelton, W.D., 1991. Simulation Modeling and Analysis. New York: McGraw-Hill.
  8. Naylor, T.H. and Finger, J.M., 1967. Verification of computer simulation models. Management Science, 14, 92-101.
  9. Nechval, N.A., 1997a. Adaptive CFAR tests for detection of a signal in noise and deflection criterion. In: Digital Signal Processing for Communication Systems, T. Wysocki, H. Razavi, & B. Honary, eds. Kluwer Academic Publishers, 177-186.
  10. Nechval, N.A., 1997b. UMPI test for adaptive signal detection. In: Proc. SPIE 3068: Signal Processing, Sensor Fusion, and Target Recognition VI, I. Kadar, ed. Orlando, Florida USA, Paper No. 3068-73, 12 pages.
  11. Nechval, N.A. and Nechval, K.N., 1998a. Characterization theorems for selecting the type of underlying distribution. In: Abstracts of Communications of the 7th Vilnius Conference on Probability Theory and Mathematical Statistics & the 22nd European Meeting of Statisticians (Vilnius, Lithuania, August 12-18). TEV, 352-353.
  12. Nechval, N.A., 1988b. A general method for constructing automated procedures for testing quickest detection of a change in quality control. Computers in Industry, 10, 1988, 177-183.
  13. Nechval, N.A. and Nechval, K.N., 1999. CFAR test for moving window detection of a signal in noise. In: Proceedings of the 5th International Symposium on DSP for Communication Systems (Perth-Scarborough, Australia, February 1-4). IEEE, 134-141.
  14. Nechval, N.A., Nechval, K.N., and Vasermanis, E.K., 2000. Technique of testing for two-phase regressions. In: Proceedings of the Second International Conference on Simulation, Gaming, Training and Business Process Reengineering in Operations, (Riga, Latvia, September 21-23). RTU, 129-133.
  15. Ottosson, F. and Håkanson, L., 1997. Presentation and analysis of a model simulating the pH response of lake liming. Ecol. Modelling, 104, 89-111.
  16. Pegden, C.P., Shannon, R.E., and Sadowski, R.P., 1990. Introduction to Simulation using SIMAN. New York: McGraw-Hill.
  17. Sargent, R.G., 1991. Simulation model verification and validation. In: Proceedings of the 1991 Winter Simulation Conference, 37-47.
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Paper Citation


in Harvard Style

Nechval N., Nechval K., Vasermanis E. and Rozite K. (2004). IDENTIFYING AN OBSERVABLE PROCESS WITH ONE OF SEVERAL SIMULATION MODELS VIA UMPI TEST . In Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO, ISBN 972-8865-12-0, pages 152-159. DOI: 10.5220/0001133101520159


in Bibtex Style

@conference{icinco04,
author={Nicholas A. Nechval and Konstantin N. Nechval and Edgars K. Vasermanis and Kristine Rozite},
title={IDENTIFYING AN OBSERVABLE PROCESS WITH ONE OF SEVERAL SIMULATION MODELS VIA UMPI TEST},
booktitle={Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,},
year={2004},
pages={152-159},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001133101520159},
isbn={972-8865-12-0},
}


in EndNote Style

TY - CONF
JO - Proceedings of the First International Conference on Informatics in Control, Automation and Robotics - Volume 3: ICINCO,
TI - IDENTIFYING AN OBSERVABLE PROCESS WITH ONE OF SEVERAL SIMULATION MODELS VIA UMPI TEST
SN - 972-8865-12-0
AU - Nechval N.
AU - Nechval K.
AU - Vasermanis E.
AU - Rozite K.
PY - 2004
SP - 152
EP - 159
DO - 10.5220/0001133101520159