IDEAS home Printed from https://ideas.repec.org/a/tsj/stataj/v3y2003i4p412-419.html
   My bibliography  Save this article

From the help desk: Local polynomial regression and Stata plugins

Author

Listed:
  • Roberto G. Gutierrez

    (StataCorp LP)

  • Jean Marie Linhart

    (StataCorp LP)

  • Jeffrey S. Pitblado

    (StataCorp LP)

Abstract

Local polynomial regression is a generalization of local mean smoothing as described by Nadaraya (1964)andWat s on (1964). Instead of fitting a local mean, one instead fits a local pth-order polynomial. Calculations for local polynomial regression are naturally more complex than those for local means, but local polynomial smooths have better statistical properties. The computational complexity may, however, be alleviated by using a Stata plugin. In this article, we describe the locpoly command for performing local polynomial regression. The calculations involved are implemented in both ado-code and with a plugin, allowing the user to assess the speed improvement obtained from using the plugin. Source code for the plugin is also provided as part of the package for this program. Copyright 2003 by StataCorp LP.

Suggested Citation

  • Roberto G. Gutierrez & Jean Marie Linhart & Jeffrey S. Pitblado, 2003. "From the help desk: Local polynomial regression and Stata plugins," Stata Journal, StataCorp LP, vol. 3(4), pages 412-419, December.
    • Handle: RePEc:tsj:stataj:v:3:y:2003:i:4:p:412-419
    as

    Download full text from publisher

    File URL: http://www.stata-journal.com/software/sj3-4/st0053/
    Download Restriction: no
    File URL: http://www.stata-journal.com/sjpdf.html?articlenum=st0053
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Rik Chakraborti & Gavin Roberts, 2023. "How price-gouging regulation undermined COVID-19 mitigation: county-level evidence of unintended consequences," Public Choice, Springer, vol. 196(1), pages 51-83, July.
    2. Austin Nichols, 2007. "Causal inference with observational data," Stata Journal, StataCorp LP, vol. 7(4), pages 507-541, December.
    3. Hudde, Ansgar & Jacob, Marita, 2022. "There’s More in the Data! Using Month-Specific Information to Estimate Changes Before and After Major Life Events," SocArXiv vueas, Center for Open Science.
    4. Carrasco, Bruno & Mukhopadhyay, Hiranya, 2014. "Reserve Bank of India’s Policy Dilemmas: Reconciling Policy Goals in Times of Turbulence," ADB Economics Working Paper Series 393, Asian Development Bank.
    5. Hazhir Rahmandad, 2014. "Human Growth and Body Weight Dynamics: An Integrative Systems Model," PLOS ONE, Public Library of Science, vol. 9(12), pages 1-22, December.
    6. Natalie Nitsche & Ansgar Hudde, 2022. "Countries embracing maternal employment opened schools sooner after Covid-19 lockdowns," MPIDR Working Papers WP-2022-008, Max Planck Institute for Demographic Research, Rostock, Germany.
    7. Shewmake, Sharon & Jarvis, Lovell, 2014. "Hybrid cars and HOV lanes," Transportation Research Part A: Policy and Practice, Elsevier, vol. 67(C), pages 304-319.
    8. Beneito, Pilar & Rochina-Barrachina, María Engracia & Sanchis, Amparo, 2014. "Learning through experience in Research & Development: An empirical analysis with Spanish firms," Technological Forecasting and Social Change, Elsevier, vol. 88(C), pages 290-305.
    9. Ansgar Hudde & Marita Jacob, 2023. "There’s More in the Data! Using Month-Specific Information to Estimate Changes Before and After Major Life Events," SOEPpapers on Multidisciplinary Panel Data Research 1184, DIW Berlin, The German Socio-Economic Panel (SOEP).
    10. Hudde, Ansgar, 2022. "The unequal cycling boom in Germany," Journal of Transport Geography, Elsevier, vol. 98(C).
    11. Simon Berset & Martin Huber & Mark Schelker, 2023. "The fiscal response to revenue shocks," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 30(3), pages 814-848, June.
    12. Hudde, Ansgar, 2023. "It's the mobility culture, stupid! Winter conditions strongly reduce bicycle usage in German cities, but not in Dutch ones," Journal of Transport Geography, Elsevier, vol. 106(C).

    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:tsj:stataj:v:3:y:2003:i:4:p:412-419. 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: Christopher F. Baum or Lisa Gilmore (email available below). General contact details of provider: http://www.stata-journal.com/ .

    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.