STR: A Seasonal-Trend Decomposition Procedure Based on Regression
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- Julius Shiskin, 1957. "Electronic Computers and Business Indicators," NBER Books, National Bureau of Economic Research, Inc, number juli57-1, February.
- Alysha M De Livera & Rob J Hyndman, 2009. "Forecasting time series with complex seasonal patterns using exponential smoothing," Monash Econometrics and Business Statistics Working Papers 15/09, Monash University, Department of Econometrics and Business Statistics.
- Alexander Dokumentov & Rob J Hyndman, 2014. "Low-dimensional decomposition, smoothing and forecasting of sparse functional data," Monash Econometrics and Business Statistics Working Papers 16/14, Monash University, Department of Econometrics and Business Statistics.
- Commandeur, Jacques J. F. & Koopman, Siem Jan & Ooms, Marius, 2011. "Statistical Software for State Space Methods," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 41(i01).
- Rob J Hyndman & Shu Fan, 2008. "Density forecasting for long-term peak electricity demand," Monash Econometrics and Business Statistics Working Papers 6/08, Monash University, Department of Econometrics and Business Statistics.
- Findley, David F, et al, 1998. "New Capabilities and Methods of the X-12-ARIMA Seasonal-Adjustment Program," Journal of Business & Economic Statistics, American Statistical Association, vol. 16(2), pages 127-152, April.
- Harvey,Andrew C., 1991.
"Forecasting, Structural Time Series Models and the Kalman Filter,"
Cambridge Books,
Cambridge University Press, number 9780521405737, January.
- Harvey,Andrew C., 1990. "Forecasting, Structural Time Series Models and the Kalman Filter," Cambridge Books, Cambridge University Press, number 9780521321969, January.
- Alexander Dokumentov & Rob J Hyndman, 2013. "Two-dimensional smoothing of mortality rates," Monash Econometrics and Business Statistics Working Papers 26/13, Monash University, Department of Econometrics and Business Statistics.
- Weinberg, Jonathan & Brown, Lawrence D. & Stroud, Jonathan R., 2007. "Bayesian Forecasting of an Inhomogeneous Poisson Process With Applications to Call Center Data," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1185-1198, December.
- Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521785167, January.
- Harvey, A C, 1985. "Trends and Cycles in Macroeconomic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 3(3), pages 216-227, June.
- McElroy Tucker S, 2010. "A Nonlinear Algorithm for Seasonal Adjustment in Multiplicative Component Decompositions," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 14(4), pages 1-23, September.
- Ruppert,David & Wand,M. P. & Carroll,R. J., 2003. "Semiparametric Regression," Cambridge Books, Cambridge University Press, number 9780521780506, January.
- Inyoung Kim & Noah D. Cohen & Raymond J. Carroll, 2003. "Semiparametric Regression Splines in Matched Case-Control Studies," Biometrics, The International Biometric Society, vol. 59(4), pages 1158-1169, December.
- Julius Shiskin, 1957. "Electronic Computers and Business Indicators," The Journal of Business, University of Chicago Press, vol. 30, pages 219-219.
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More about this item
Keywords
time series decomposition; seasonal data; Tikhonov regularisation; ridge regression; LASSO; STL; TBATS; X-12-ARIMA; BSM;All these keywords.
JEL classification:
- C10 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2015-06-20 (Econometrics)
- NEP-ETS-2015-06-20 (Econometric Time Series)
- NEP-FOR-2015-06-20 (Forecasting)
- NEP-ORE-2015-06-20 (Operations Research)
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