IDEAS home Printed from https://ideas.repec.org/a/eee/jomega/v28y2000i2p215-221.html
   My bibliography  Save this article

On modeling time series data using spreadsheets

Author

Listed:
  • Ragsdale, Cliff T.
  • Plane, Donald R.

Abstract

Linear regression analysis has long been used to estimate the parameters of various types of times series (TS) models. In some cases, the application of traditional regression-based techniques to TS data does not produce the optimal values of the parameters being estimated. The nonlinear optimization tool (known as Solver) built into today's electronic spreadsheets can alleviate these estimation problems as well as simplify the process of modeling many types of TS problems. This paper presents two examples of TS problems where Solver performs better than regression-based TS techniques. It also encourages educators to reevaluate these and other traditional TS techniques in light of Solver's capabilities.

Suggested Citation

  • Ragsdale, Cliff T. & Plane, Donald R., 2000. "On modeling time series data using spreadsheets," Omega, Elsevier, vol. 28(2), pages 215-221, April.
  • Handle: RePEc:eee:jomega:v:28:y:2000:i:2:p:215-221
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0305-0483(99)00038-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Howard-Pitney, B. & Winkleby, M.A. & Albright, C.L. & Bruce, B. & Fortmann, S.P., 1997. "The Stanford Nutrition Action Program: A dietary fat intervention for low-literacy adults," American Journal of Public Health, American Public Health Association, vol. 87(12), pages 1971-1976.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Rasmussen, Rasmus, 2004. "On time series data and optimal parameters," Omega, Elsevier, vol. 32(2), pages 111-120, April.

    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.
    1. Wong-Parodi, Gabrielle & Bruine de Bruin, Wändi & Canfield, Casey, 2013. "Effects of simplifying outreach materials for energy conservation programs that target low-income consumers," Energy Policy, Elsevier, vol. 62(C), pages 1157-1164.

    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:eee:jomega:v:28:y:2000:i:2:p:215-221. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/375/description#description .

    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.