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Representation of user transaction processing behavior with a state transition matrix
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Source Winter Simulation Conference archive
Proceedings of the 24th conference on Winter simulation table of contents
Arlington, Virginia, United States
Pages: 1223 - 1231  
Year of Publication: 1992
ISBN:0-7803-0798-4
Authors
Sponsors
ASA : American Statistical Association
NIST : National Institue of Standards & Technology
IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
ACM: Association for Computing Machinery
ORSA : Operations Research Society of America
SIGSIM: ACM Special Interest Group on Simulation and Modeling
TIMS :
IIE : Institute of Industrial Engineers
SCS : Society for Computer Simulation
Publisher
ACM  New York, NY, USA
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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Anderson, T.W., and Goodman, L.A. 1957. Statistical Inference about Markov Chains. Annals of Mathematical Statistics 28: 89-110.
 
2
Bhat, U.N., 1984. Elements of Applied Stochastic Processes, Second Edition. New York: John Wiley and Sons.
 
3
Chatfield, C. 1973. Statistical Inference Regarding Markov Chain Models. Applied Statistics 22: 7-20.
 
4
Eier, R., 1989. Discrete Stochastic models by means of Markov Chains. ITG-Fachbericht 107: 167-173.
 
5
jain, R. 1991. The Art of Computer Systems Performance Analysis. New York: John Wiley and Sons.
 
6
Kelton, C.M.L., and Kelton, W.D. 1985. Development of Specific Hypothesis Tests for Estimated Markov Chains. Journal of Statistical Computation and Simulation 23: 15-23.
 
7
Kelton, C.M.L., and Kelton, W.D. 1987. Comparison of Hypothesis testing techniques for Markov processes Estimated from Micro versus Macro data. Annals of Operations Research 8: 175-194.
 
8
Kelton, C.M.L., and Kelton, W.D 1991. A Comparison of Micro versus Macro Point Estimators for Markov- Process Models. Journal of Statistical Computation and Simulation 38:201-210
 
9
Krieger, U.R., Mfiller-Clostermann, B., and SczittnJck, M. 1990. Modeling and Analysis of Communications Systems Based on Computational Methods for Markov Chains. IEEE Journal on Selected Areas in Communications 8" 1630-1648.
 
10
Vasegji, S.V. 1991. Hidden Markov Models with Duration-Dependent State Transition Probabilities. Electronics Letters 27: 625-626.


Collaborative Colleagues:
William S. Keezer: colleagues
Andrew P. Fenic: colleagues
Barry L. Nelson: colleagues