IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v25y1976i2p107-116.html
   My bibliography  Save this article

Interpolating Time Series with Application to the Estimation of Holiday Effects on Electricity Demand

Author

Listed:
  • S. R. Brubacher
  • G. Tunnicliffe Wilson

Abstract

The least squares principle is applied to the problem of estimating missing points in a time series represented by a Box‐Jenkins seasonal model. The procedure developed is used to estimate the effect of one‐day national holidays on hourly electricity demand. This is done by interpolating over the holiday period using unaffected demand observations from both before and after this period. The ratio of the actual demand to the estimated normal demand, recorded for the same holiday period over successive years, may then be used to forecast the effect on demand of future holidays.

Suggested Citation

  • S. R. Brubacher & G. Tunnicliffe Wilson, 1976. "Interpolating Time Series with Application to the Estimation of Holiday Effects on Electricity Demand," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 25(2), pages 107-116, June.
    • Handle: RePEc:bla:jorssc:v:25:y:1976:i:2:p:107-116
    DOI: 10.2307/2346678
    as

    Download full text from publisher

    File URL: https://doi.org/10.2307/2346678
    Download Restriction: no
    File URL: https://libkey.io/10.2307/2346678?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gómez, Víctor & Maravall, Agustín & Peña, Daniel, 1993. "Computing missing values in time series," DES - Working Papers. Statistics and Econometrics. WS 3737, Universidad Carlos III de Madrid. Departamento de Estadística.
    2. Pascal Bondon, 2005. "Influence of Missing Values on the Prediction of a Stationary Time Series," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(4), pages 519-525, July.
    3. Gómez, Víctor & Maravall, Agustín & Peña, Daniel, 1997. "Missing observations in ARIMA models: skipping strategy versus additive outlier approach," DES - Working Papers. Statistics and Econometrics. WS 10576, Universidad Carlos III de Madrid. Departamento de Estadística.
    4. Comincioli, Nicola & Vergalli, Sergio, 2020. "Effects of Carbon Tax on Electricity Price Volatility: Empirical Evidences from the Australian Market," 2030 Agenda 305205, Fondazione Eni Enrico Mattei (FEEM).
    5. Delicado, Pedro, 1995. "Predicción con datos faltantes: aplicación a un caso real," DES - Documentos de Trabajo. Estadística y Econometría. DS 3583, Universidad Carlos III de Madrid. Departamento de Estadística.
    6. Maravall, Agustín & Peña, Daniel, 1992. "Missing observations and additive outliers in time series models," UC3M Working papers. Economics 2888, Universidad Carlos III de Madrid. Departamento de Economía.
    7. Pedro Delicado & Ana Justel, 1997. "Forecasting with missing data: Application to a real case," Economics Working Papers 213, Department of Economics and Business, Universitat Pompeu Fabra.
    8. Kasahara, Yukio & Pourahmadi, Mohsen & Inoue, Akihiko, 2009. "Duals of random vectors and processes with applications to prediction problems with missing values," Statistics & Probability Letters, Elsevier, vol. 79(14), pages 1637-1646, July.
    9. Alonso, Andres M. & Sipols, Ana E., 2008. "A time series bootstrap procedure for interpolation intervals," Computational Statistics & Data Analysis, Elsevier, vol. 52(4), pages 1792-1805, January.
    10. Gomez, Victor & Maravall, Agustin & Pena, Daniel, 1998. "Missing observations in ARIMA models: Skipping approach versus additive outlier approach," Journal of Econometrics, Elsevier, vol. 88(2), pages 341-363, November.
    11. Luis J. Alvarez & Juan C. Delrieu & Antoni Espasa, 1992. "Aproximación lineal por tramos a comportamientos no lineales : estimación de señales de nivel y crecimiento," Working Papers 9226, Banco de España.
    12. Cheng, R. & Pourahmadi, M., 1997. "Prediction with incomplete past and interpolation of missing values," Statistics & Probability Letters, Elsevier, vol. 33(4), pages 341-346, May.
    13. Zudi Lu & Y. Hui, 2003. "L 1 linear interpolator for missing values in time series," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 55(1), pages 197-216, March.
    14. Guerrero, Víctor M. & Peña, Daniel, 1995. "Linear combination of information in time series analysis," DES - Working Papers. Statistics and Econometrics. WS 10340, Universidad Carlos III de Madrid. Departamento de Estadística.
    15. Justel, Ana & Peña, Daniel & Sánchez, María Jesús, 1994. "Grupos atípicos en modelos econométricos," DES - Documentos de Trabajo. Estadística y Econometría. DS 10755, Universidad Carlos III de Madrid. Departamento de Estadística.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    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:bla:jorssc:v:25:y:1976:i:2:p:107-116. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.