{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T22:26:35Z","timestamp":1740176795979,"version":"3.37.3"},"reference-count":26,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,1,3]],"date-time":"2019-01-03T00:00:00Z","timestamp":1546473600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["LE-1416\/17-2"],"award-info":[{"award-number":["LE-1416\/17-2"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100008530","name":"European Regional Development Fund","doi-asserted-by":"publisher","award":["100320127"],"award-info":[{"award-number":["100320127"]}],"id":[{"id":"10.13039\/501100008530","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["CRC 912 (HAEC)"],"award-info":[{"award-number":["CRC 912 (HAEC)"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Int J Data Sci Anal"],"published-print":{"date-parts":[[2019,9]]},"DOI":"10.1007\/s41060-018-00169-7","type":"journal-article","created":{"date-parts":[[2019,1,3]],"date-time":"2019-01-03T11:49:54Z","timestamp":1546516194000},"page":"165-181","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["CSAR: the cross-sectional autoregression model for short and long-range forecasting"],"prefix":"10.1007","volume":"8","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5334-059X","authenticated-orcid":false,"given":"Claudio","family":"Hartmann","sequence":"first","affiliation":[]},{"given":"Franziska","family":"Ressel","sequence":"additional","affiliation":[]},{"given":"Martin","family":"Hahmann","sequence":"additional","affiliation":[]},{"given":"Dirk","family":"Habich","sequence":"additional","affiliation":[]},{"given":"Wolfgang","family":"Lehner","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,1,3]]},"reference":[{"issue":"2","key":"169_CR1","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1002\/for.3980080204","volume":"8","author":"M Aldrin","year":"1989","unstructured":"Aldrin, M., Damsleth, E.: Forecasting non-seasonal time series with missing observations. J. Forecast. 8(2), 97\u2013116 (1989). \n                    https:\/\/doi.org\/10.1002\/for.3980080204","journal-title":"J. Forecast."},{"key":"169_CR2","unstructured":"Bemdt, D.J., Clifford, J.: Using dynamic time warping to find patterns in time series. In: AAAIWS\u201994 Proceedings of the 3rd International Conference on Knowledge Discovery and Data Mining, pp. 359\u2013370 (1994)"},{"key":"169_CR3","doi-asserted-by":"publisher","DOI":"10.1002\/9781118619193","volume-title":"Time Series Analysis: Forecasting and Control (Wiley Series in Probability and Statistics)","author":"GEP Box","year":"2008","unstructured":"Box, G.E.P., Jenkins, G.M., Reinsel, G.C.: Time Series Analysis: Forecasting and Control (Wiley Series in Probability and Statistics). Wiley, New York (2008)"},{"key":"169_CR4","doi-asserted-by":"publisher","DOI":"10.1201\/9781420036206","volume-title":"Time-Series Forecasting","author":"C Chatfield","year":"2000","unstructured":"Chatfield, C.: Time-Series Forecasting. Chapman & Hall\/CRC Press, Boca Raton (2000)"},{"issue":"3","key":"169_CR5","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1057\/jors.1972.50","volume":"23","author":"JD Croston","year":"1972","unstructured":"Croston, J.D.: Forecasting and stock control for intermittent demands. Oper. Res. Q. 23(3), 289\u2013303 (1972). \n                    https:\/\/doi.org\/10.2307\/3007885","journal-title":"Oper. Res. Q."},{"issue":"1","key":"169_CR6","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1108\/02635570110365952","volume":"101","author":"G Fliedner","year":"2001","unstructured":"Fliedner, G.: Hierarchical forecasting: issues and use guidelines. Ind. Manag. Data Syst. 101(1), 5\u201312 (2001). \n                    https:\/\/doi.org\/10.1108\/02635570110365952","journal-title":"Ind. Manag. Data Syst."},{"issue":"1","key":"169_CR7","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1214\/aos\/1176347963","volume":"19","author":"JH Friedman","year":"1991","unstructured":"Friedman, J.H.: Multivariate adaptive regression splines. Ann. Stat. 19(1), 1\u201367 (1991). \n                    https:\/\/doi.org\/10.1214\/aos\/1176347963","journal-title":"Ann. Stat."},{"issue":"5","key":"169_CR8","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1214\/aos\/1013203451","volume":"29","author":"JH Friedman","year":"2001","unstructured":"Friedman, J.H.: Greedy function approximation: a gradient boosting machine. Ann. Stat. 29(5), 1189\u20131232 (2001)","journal-title":"Ann. Stat."},{"key":"169_CR9","unstructured":"GOFLEX Project. \n                    http:\/\/goflex-project.eu\/\n                    \n                   (11.02.2017)"},{"key":"169_CR10","doi-asserted-by":"crossref","unstructured":"Hartmann, C., Hahmann, M., Habich, D., Lehner, W.: CSAR: The Cross-sectional autoregression model. In: 2017 International Conference on Data Science and Advanced Analytics (DSAA 2017), Tokyo, pp. 1\u201310 (2017)","DOI":"10.1109\/DSAA.2017.27"},{"key":"169_CR11","doi-asserted-by":"publisher","unstructured":"Hartmann, C., Hahmann, M., Rosenthal, F., Lehner, W.: Exploiting big data in time series forecasting : a cross-sectional approach. In: IEEE International Conference on Data Science and Advanced Analytics (DSAA), 2015, Paris, pp. 1\u201310 (2015). \n                    https:\/\/doi.org\/10.1109\/DSAA.2015.7344786","DOI":"10.1109\/DSAA.2015.7344786"},{"issue":"1","key":"169_CR12","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1016\/j.ijforecast.2003.09.015","volume":"20","author":"CC Holt","year":"2004","unstructured":"Holt, C.C.: Forecasting seasonals and trends by exponentially weighted moving averages. Int. J. Forecast. 20(1), 5\u201310 (2004). \n                    https:\/\/doi.org\/10.1016\/j.ijforecast.2003.09.015","journal-title":"Int. J. Forecast."},{"issue":"3","key":"169_CR13","doi-asserted-by":"publisher","first-page":"1","DOI":"10.18637\/jss.v027.i03","volume":"27","author":"RJ Hyndman","year":"2008","unstructured":"Hyndman, R.J., Khandakar, Y.: Automatic time series for forecasting: the forecast package for R. J. Stat. Softw. 27(3), 1\u201322 (2008)","journal-title":"J. Stat. Softw."},{"key":"169_CR14","unstructured":"IJCAI: IJCAI 2017 - Data Mining Contest (08.02.2017). \n                    http:\/\/tb.am\/s0a3o"},{"key":"169_CR15","unstructured":"Irish Social Science Data Archive (ISSDA): CER Smart Metering Project. The Commission for Energy Regulation (CER) (28.04.2015). \n                    www.ucd.ie\/issda"},{"key":"169_CR16","unstructured":"Levy, D.: Introduction to Numerical Analysis (2010)"},{"issue":"5","key":"169_CR17","doi-asserted-by":"publisher","first-page":"303","DOI":"10.1002\/for.989","volume":"25","author":"TM McCarthy","year":"2006","unstructured":"McCarthy, T.M., Davis, D.F., Golicic, S.L., Mentzer, J.T.: The evolution of sales forecasting management: a 20-year longitudinal study of forecasting practices. J. Forecast. 25(5), 303\u2013324 (2006). \n                    https:\/\/doi.org\/10.1002\/for.989","journal-title":"J. Forecast."},{"key":"169_CR18","doi-asserted-by":"publisher","unstructured":"Neupane, B., Pedersen, T.B., Thiesson, B.: Towards flexibility detection in device-level energy consumption. In: Woon, W.L., Aung, Z., Madnick, S. (eds.) Data Analytics for Renewable Energy Integration: Proceedings of the Second ECML PKDD Workshop, DARE 2014, vol. 8817, Nancy, pp. 1\u201316 (2014). \n                    https:\/\/doi.org\/10.1007\/978-3-319-13290-7_1","DOI":"10.1007\/978-3-319-13290-7_1"},{"key":"169_CR19","unstructured":"R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2014). \n                    http:\/\/www.R-project.org\/"},{"issue":"3","key":"169_CR20","doi-asserted-by":"publisher","first-page":"309","DOI":"10.1002\/for.3980030308","volume":"3","author":"T Riise","year":"1984","unstructured":"Riise, T., Tjostheim, D.: Theory and practice of multivariate arma forecasting. J. Forecast. 3(3), 309\u2013317 (1984). \n                    https:\/\/doi.org\/10.1002\/for.3980030308","journal-title":"J. Forecast."},{"key":"169_CR21","unstructured":"Robert, N.: Statistical forecasting: notes on regression and time series analysis. \n                    http:\/\/people.duke.edu\/~rnau\/411home.htm\n                    \n                  . Accessed 09.11.2016"},{"issue":"6","key":"169_CR22","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1002\/for.963","volume":"24","author":"L Shenstone","year":"2005","unstructured":"Shenstone, L., Hyndman, R.J.: Stochastic models underlying Croston\u2019s method for intermittent demand forecasting. J. Forecast. 24(6), 389\u2013402 (2005)","journal-title":"J. Forecast."},{"issue":"376","key":"169_CR23","doi-asserted-by":"publisher","first-page":"802","DOI":"10.1080\/01621459.1981.10477728","volume":"76","author":"GC Tiao","year":"1981","unstructured":"Tiao, G.C., Box, G.E.P.: Modeling multiple time series with applications. J. Am. Stat. Assoc. 76(376), 802\u2013816 (1981). \n                    https:\/\/doi.org\/10.1080\/01621459.1981.10477728","journal-title":"J. Am. Stat. Assoc."},{"key":"169_CR24","unstructured":"Universal Smart Energy Framework (USEF). \n                    www.usef.energy\n                    \n                   (11.02.2017)"},{"key":"169_CR25","unstructured":"VDE Verband der Elektrotechnik Elektronik Informationstechnik e.V.: Messwesen Strom (Metering Code); VDE-AR-N 4400 (2011)"},{"key":"169_CR26","volume-title":"Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems","author":"O Vermesan","year":"2013","unstructured":"Vermesan, O., Friess, P.: Internet of Things: Converging Technologies for Smart Environments and Integrated Ecosystems. River Publishers, Aalborg (2013)"}],"container-title":["International Journal of Data Science and Analytics"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s41060-018-00169-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s41060-018-00169-7\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s41060-018-00169-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,1,2]],"date-time":"2020-01-02T19:22:53Z","timestamp":1577992973000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s41060-018-00169-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,1,3]]},"references-count":26,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,9]]}},"alternative-id":["169"],"URL":"https:\/\/doi.org\/10.1007\/s41060-018-00169-7","relation":{},"ISSN":["2364-415X","2364-4168"],"issn-type":[{"type":"print","value":"2364-415X"},{"type":"electronic","value":"2364-4168"}],"subject":[],"published":{"date-parts":[[2019,1,3]]},"assertion":[{"value":"6 December 2017","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 December 2018","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"3 January 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}