On sample size and precision in ordinary least squares
AbstractAn expression relating estimation precision in the classical linear model to the number of parameters k and the sample size n is illustrated. A rule of thumb for the sample size is suggested.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Taylor & Francis Journals in its journal Journal of Applied Statistics.
Volume (Year): 28 (2001)
Issue (Month): 5 ()
Contact details of provider:
Web page: http://www.tandfonline.com/CJAS20
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Montgomery, David B & Morrison, Donald G, 1973. "A Note on Adjusting R2," Journal of Finance, American Finance Association, vol. 28(4), pages 1009-13, September.
- Peter Kennedy, 2003. "A Guide to Econometrics, 5th Edition," MIT Press Books, The MIT Press, edition 5, volume 1, number 026261183x, June.
- Koenker, Roger, 1988. "Asymptotic Theory and Econometric Practice," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 3(2), pages 139-47, April.
- Ramsey, James B. & Montenegro, Alvaro, 1992. "Identification and estimation of noninvertible non-Gaussian MA(q) processes," Journal of Econometrics, Elsevier, vol. 54(1-3), pages 301-320.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Michael McNulty).
If references are entirely missing, you can add them using this form.