Smoothing time series for input and output analysis in system simulation experiments (tutorial session)

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Smoothing time series for input and output analysis in system simulation experiments (tutorial session)

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Winter Simulation Conference archive
Proceedings of the 22nd conference on Winter simulation table of contents

New Orleans, Louisiana, United States

Pages: 46 - 48

Year of Publication: 1990

ISBN:0-911801-72-3

Authors

Peter A. W. Lewis	Department of Operations Research, Naval Postgraduate School, Monterey, California
James G. Stevens	United States Army, Fort Leavenworth, Kansas

Sponsors

IEEE-CS : Computer Society
IEEE-SMCS : Systems, Man & Cybernetics Society
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
ASA : American Statistical Association
NIST : National Institue of Standards & Technology

Publisher

IEEE Press Piscataway, NJ, 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	Altman, N.S. (1989), "Kernel Smoothing of Data with Correlated Errors," Submitted to Journal of the American Statistical Association.
	2	Altman, N.S. (1990), Simultaneous Estimation of the Mean and Correlation Functions in Nonpararnetric Regression Problems with AR(1) Errors, submitted for publication.
	3	Craven, P. and G. Whaba (1979), "Smoothing Noisy Data with Spline Functions. Estimating the Correct Degree of Smoothing by the Method of Generalized Cross-Validation," Numerische Mathematik 31,317-403.
	4	Friedman, J.H. (1988), Multivariate Adaptive Regression Splines, Submitted for publication.
	5	Kendall, M.G., Stuart, A. and J. Keith Oral (1987), The Advanced Theory of Statistics: Vol. 3, Design and Analysis and Time Series. Oxford University Press: Oxford, England.
	6	Lewis, P.A.W., and J.G. Stevens (1990), "Nonlinear Modelling of Time Series using Multivariate Adaptive Regression Splines (MARS)," Submitted to the Journal of the American Statistical Association.
	7	Morgan, J.N. and J.A. Sonquist (1963), "Problems in the Analysis of Survey Data, and a Proposal," Journal of the American Statistical Association 58, 415-434.
	8	Silverman, B.W. (1985), "Some Aspects of the Spline Smoothing Approach to Non-Parametric Regression Curve Fitting," Journal of the Royal Statistical Society, Series B, 47, 1, 1-52.