Sax, Christoph and Steiner, Peter (2013): Temporal Disaggregation of Time Series. Published in: The R Journal , Vol. 5, No. 2 (December 2013): pp. 80-87.
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Abstract
Temporal disaggregation methods are used to disaggregate low frequency time series to higher frequency series, where either the sum, the average, the first or the last value of the resulting high frequency series is consistent with the low frequency series. Temporal disaggregation can be performed with or without one or more high frequency indicator series. The package tempdisagg is a collection of several methods for temporal disaggregation.
Item Type: | MPRA Paper |
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Original Title: | Temporal Disaggregation of Time Series |
English Title: | Temporal Disaggregation of Time Series |
Language: | English |
Keywords: | temporal disaggregation, time series, Chow-Lin, Denton, Fernandez, Litterman |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C13 - Estimation: General C - Mathematical and Quantitative Methods > C6 - Mathematical Methods ; Programming Models ; Mathematical and Simulation Modeling > C65 - Miscellaneous Mathematical Tools C - Mathematical and Quantitative Methods > C8 - Data Collection and Data Estimation Methodology ; Computer Programs > C87 - Econometric Software |
Item ID: | 53389 |
Depositing User: | Dr. Peter Steiner |
Date Deposited: | 06 Mar 2014 14:19 |
Last Modified: | 29 Sep 2019 00:46 |
References: | L. Barbone, G. Bodo, and I. Visco. Costi e profitti nell’industria in senso stretto: Un’analisi su serie trimestrali, 1970–1980. Bolletino della Banca d’Italia, pages 467–510, 1981. R. Barcellan, T. Di Fonzo, D. Raffaele, V. Staplehurst, and D. Buono. Ecotrim: A Program for Temporal Disaggregation of Time Series, 2003. URL https://circabc.europa.eu/w/browse/c6049bc0-c6334cab-9811-b476ffe08370. Version 1.01. J. Bournay and G. Laroque. Réflexions sur la méthode d’élaboration des comptes trimestriels. Annales de l’INSÉÉ, 36:3–30, 1979. G. C. Chow and A.-L. Lin. Best linear unbiased interpolation, distribution, and extrapolation of time series by related series. The Review of Economics and Statistics, 53(4):372–375, Nov. 1971. E. B. Dagum and P. A. Cholette. Benchmarking, Temporal Distribution, and Reconciliation Methods for Time Series. Lecture Notes in Statistics. Springer-Verlag, New York, 2006. F. T. Denton. Adjustment of monthly or quarterly series to annual totals: An approach based on quadratic minimization. Journal of the American Statistical Association, 66:99–102, Mar. 1971. T. Di Fonzo. Temporal disaggregation of a system of time series when the aggregate is known: Optimal vs. adjustment methods. In Workshop on Quarterly National Accounts, pages 63–77, Paris, Dec. 1994. Eurostat. T. Doan. Disaggregate: A General Procedure for Interpolation, 2008. URL www.estima.com/procs_perl/disaggregate.src. RATS library version Apr. 07, 2008. R. B. Fernández. A methodological note on the estimation of time series. The Review of Economics and Statistics, 63(3):471–476, 1981. R. B. Litterman. A random walk, Markov model for the distribution of time series. Journal of Business & Economic Statistics, 1(2):169–173, 1983. C. C. Paige. Fast numerically stable computations for generalized linear least squares problems. SIAM Journal on Numerical Analysis, 16(1):165–171, 1979. E. M. Quilis. Temporal Disaggregation Library, 2012. URL www.mathworks.com/matlabcentral/fileexchange/24438-. Matlab library version May 08, 2012. C. Sax and P. Steiner. tempdisagg: Methods for Temporal Disaggregation and Interpolation of Time Series, 2013. URL http://CRAN.R-project.org/package=tempdisagg. R package version 0.22. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/53389 |