IDEAS home Printed from https://ideas.repec.org/
MyIDEAS: Login to save this paper or follow this series

Nonparametric Density Estimation for Stratified Samples

  • Robert Breunig

    ()

In this paper, we consider the non-parametric, kernel estimate of the density, f(x), for data drawn from stratified samples. Much of the data used by social scientists is gathered in some type of complex survey violating the usual assumptions of independently and identically distributed data. Such effects induced by the survey structure are rarely considered in the literature on non-parametric density estimation, yet they may have serious consequences for our analysis, as shown in this paper. A weighted estimator is developed which provides asymptotically unbiased density estimation for stratified samples. A data-based method for choosing the optimal bandwidth is suggested, using information on withinstratum variances and means. The weighted estimator and proposed bandwidth are shown to give smaller mean squared error for stratified samples than an un-weighted estimator and a commonly used method of choosing the bandwidth. Surprisingly, the single bandwidth outperforms optimally choosing stratum-specific bandwidths in some cases. Several illustrations from simulation are provided. We also show that the optimal sampling scheme in this case is always stratified sampling proportional to size, irrespective of the stratum-specific densities

If 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.

File URL: http://cbe.anu.edu.au/researchpapers/econ/wp459.pdf
Download Restriction: no

Paper provided by Australian National University, College of Business and Economics, School of Economics in its series ANU Working Papers in Economics and Econometrics with number 2005-459.

as
in new window

Length: 42 pages
Date of creation: Feb 2001
Date of revision: Nov 2005
Handle: RePEc:acb:cbeeco:2005-459
Contact details of provider: Postal: Canberra, ACT 2601
Phone: +61 2 6125 3807
Fax: +61 2 6125 0744
Web page: http://rse.anu.edu.au/
Email:


More information through EDIRC

References listed on IDEAS
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.:

as in new window
  1. Robert Breunig, 2001. "Density Estimation For Clustered Data," Econometric Reviews, Taylor & Francis Journals, vol. 20(3), pages 353-367.
  2. repec:cup:cbooks:9780521355643 is not listed on IDEAS
  3. repec:cup:cbooks:9780521586115 is not listed on IDEAS
Full references (including those not matched with items on IDEAS)

This item is not listed on Wikipedia, on a reading list or among the top items on IDEAS.

When requesting a correction, please mention this item's handle: RePEc:acb:cbeeco:2005-459. See general information about how to correct material in RePEc.

For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ()

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 references are entirely missing, you can add them using this form.

If the full references list an item that is present in RePEc, but the system did not link 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 profile, as there may be some citations waiting for confirmation.

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

This information is provided to you by IDEAS at the Research Division of the Federal Reserve Bank of St. Louis using RePEc data.