Conditional Normalization in Time Series Analysis
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- Hyndman, Rob J. & Khandakar, Yeasmin, 2008.
"Automatic Time Series Forecasting: The forecast Package for R,"
Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
- Rob J. Hyndman & Yeasmin Khandakar, 2007. "Automatic time series forecasting: the forecast package for R," Monash Econometrics and Business Statistics Working Papers 6/07, Monash University, Department of Econometrics and Business Statistics.
- Guillaume Bal & Etienne Rivot & Jean-Luc Baglinière & Jonathan White & Etienne Prévost, 2014. "A Hierarchical Bayesian Model to Quantify Uncertainty of Stream Water Temperature Forecasts," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-24, December.
- Simon N. Wood, 2003. "Thin plate regression splines," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 95-114, February.
- Catherine Leigh & Sevvandi Kandanaarachchi & James M McGree & Rob J Hyndman & Omar Alsibai & Kerrie Mengersen & Erin E Peterson, 2019. "Predicting sediment and nutrient concentrations from high-frequency water-quality data," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-22, August.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Santos-Fernandez, Edgar & Ver Hoef, Jay M. & Peterson, Erin E. & McGree, James & Isaak, Daniel J. & Mengersen, Kerrie, 2022. "Bayesian spatio-temporal models for stream networks," Computational Statistics & Data Analysis, Elsevier, vol. 170(C).
- Lingbing Feng & Yanlin Shi, 2018. "Forecasting mortality rates: multivariate or univariate models?," Journal of Population Research, Springer, vol. 35(3), pages 289-318, September.
- Amara-Ouali, Yvenn & Fasiolo, Matteo & Goude, Yannig & Yan, Hui, 2023. "Daily peak electrical load forecasting with a multi-resolution approach," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1272-1286.
- Daniel R. Kowal & David S. Matteson & David Ruppert, 2019. "Functional Autoregression for Sparsely Sampled Data," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 37(1), pages 97-109, January.
- M.L. Nores & M.P. Díaz, 2016. "Bootstrap hypothesis testing in generalized additive models for comparing curves of treatments in longitudinal studies," Journal of Applied Statistics, Taylor & Francis Journals, vol. 43(5), pages 810-826, April.
- Gkillas, Konstantinos & Gupta, Rangan & Pierdzioch, Christian, 2020.
"Forecasting realized oil-price volatility: The role of financial stress and asymmetric loss,"
Journal of International Money and Finance, Elsevier, vol. 104(C).
- Konstantinos Gkillas & Rangan Gupta & Christian Pierdzioch, 2019. "Forecasting Realized Oil-Price Volatility: The Role of Financial Stress and Asymmetric Loss," Working Papers 201903, University of Pretoria, Department of Economics.
- Rob Hyndman & Heather Booth & Farah Yasmeen, 2013.
"Coherent Mortality Forecasting: The Product-Ratio Method With Functional Time Series Models,"
Demography, Springer;Population Association of America (PAA), vol. 50(1), pages 261-283, February.
- Rob J Hyndman & Heather Booth & Farah Yasmeen, 2011. "Coherent Mortality Forecasting The Product-ratio Method with Functional Time Series Models," Working Papers 201116, ARC Centre of Excellence in Population Ageing Research (CEPAR), Australian School of Business, University of New South Wales.
- Rob J Hyndman & Heather Booth & Farah Yasmeen, 2011. "Coherent mortality forecasting: the product-ratio method with functional time series models," Monash Econometrics and Business Statistics Working Papers 1/11, Monash University, Department of Econometrics and Business Statistics.
- Nahapetyan Yervand, 2019. "The benefits of the Velvet Revolution in Armenia: Estimation of the short-term economic gains using deep neural networks," Central European Economic Journal, Sciendo, vol. 6(53), pages 286-303, January.
- Barrow, Devon & Kourentzes, Nikolaos, 2018. "The impact of special days in call arrivals forecasting: A neural network approach to modelling special days," European Journal of Operational Research, Elsevier, vol. 264(3), pages 967-977.
- Georgios Gioldasis & Antonio Musolesi & Michel Simioni, 2020. "Model uncertainty, nonlinearities and out-of-sample comparison: evidence from international technology diffusion," Working Papers hal-02790523, HAL.
- Dombi, József & Jónás, Tamás & Tóth, Zsuzsanna Eszter, 2018. "Modeling and long-term forecasting demand in spare parts logistics businesses," International Journal of Production Economics, Elsevier, vol. 201(C), pages 1-17.
- Amita Gajewar & Gagan Bansal, 2016. "Revenue Forecasting for Enterprise Products," Papers 1701.06624, arXiv.org.
- Tao XIONG & Chongguang LI & Yukun BAO, 2017. "An improved EEMD-based hybrid approach for the short-term forecasting of hog price in China," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 63(3), pages 136-148.
- Pieter van der Spek & Chris Verhoef, 2014. "Balancing Time‐to‐Market and Quality in Embedded Systems," Systems Engineering, John Wiley & Sons, vol. 17(2), pages 166-192, June.
- Hewamalage, Hansika & Bergmeir, Christoph & Bandara, Kasun, 2021. "Recurrent Neural Networks for Time Series Forecasting: Current status and future directions," International Journal of Forecasting, Elsevier, vol. 37(1), pages 388-427.
- Hyndman, Rob J. & Ahmed, Roman A. & Athanasopoulos, George & Shang, Han Lin, 2011.
"Optimal combination forecasts for hierarchical time series,"
Computational Statistics & Data Analysis, Elsevier, vol. 55(9), pages 2579-2589, September.
- Rob J. Hyndman & Roman A. Ahmed & George Athanasopoulos, 2007. "Optimal combination forecasts for hierarchical time series," Monash Econometrics and Business Statistics Working Papers 9/07, Monash University, Department of Econometrics and Business Statistics.
- Fang, Lei & Härdle, Wolfgang Karl, 2015. "Stochastic population analysis: A functional data approach," SFB 649 Discussion Papers 2015-007, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
- Kourentzes, Nikolaos & Petropoulos, Fotios & Trapero, Juan R., 2014. "Improving forecasting by estimating time series structural components across multiple frequencies," International Journal of Forecasting, Elsevier, vol. 30(2), pages 291-302.
- Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Mawuli K. Segnon, 2015.
"Forecasting the price of gold,"
Applied Economics, Taylor & Francis Journals, vol. 47(39), pages 4141-4152, August.
- Hossein Hassani & Emmanuel Sirimal Silva & Rangan Gupta & Mawuli K. Segnon, 2014. "Forecasting the Price of Gold," Working Papers 201428, University of Pretoria, Department of Economics.
- Thomas Horvath & Peter Huber & Ulrike Huemer & Helmut Mahringer & Philipp Piribauer & Mark Sommer & Stefan Weingärtner, 2022. "Mittelfristige Beschäftigungsprognose für Österreich und die Bundesländer. Berufliche und sektorale Veränderungen 2021 bis 2028," WIFO Studies, WIFO, number 70720.
More about this item
Keywords
conditional normalization; missing value imputation; conditional autocorrelation; conditional cross-correlation; lag time estimation; stream data; water quality;All these keywords.
NEP fields
This paper has been announced in the following NEP Reports:- NEP-ECM-2023-11-20 (Econometrics)
- NEP-ETS-2023-11-20 (Econometric Time Series)
- NEP-FOR-2023-11-20 (Forecasting)
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:msh:ebswps:2023-10. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Professor Xibin Zhang (email available below). General contact details of provider: https://edirc.repec.org/data/dxmonau.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.