IDEAS home Printed from https://ideas.repec.org/p/ags/unasrr/234380.html
   My bibliography  Save this paper

The Theory and Practice of Maximal Brewer Selection with Poisson PRN Sampling

Author

Listed:
  • Kott, Phillip S.
  • Bailey, Jeffrey T.

Abstract

K.R.W. Brewer suggests that when estimating the total of a single item for which there is control (auxiliary) data, one employ a ratio or regression estimator and draw the sample using probabilities proportional to the control values raised to a power between 1/2 and 1. Brewer's sample selection scheme can be expanded to multiple targets by drawing overlapping Poisson samples for a number of items simultaneously using permanent random numbers (PRN's). W e can call the result an example of "Maximal Brewer Selection" (MBS). This paper develops the theory behind MBS and the calibration estimator rendering it practical. It goes on to describe ho w this estimation strategy is being used at the National Agricultural Statistics Service.

Suggested Citation

  • Kott, Phillip S. & Bailey, Jeffrey T., 2000. "The Theory and Practice of Maximal Brewer Selection with Poisson PRN Sampling," NASS Research Reports 234380, United States Department of Agriculture, National Agricultural Statistics Service.
    • Handle: RePEc:ags:unasrr:234380
    DOI: 10.22004/ag.econ.234380
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/234380/files/icespap2c8.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.234380?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
    ---><---

    References listed on IDEAS

    as
    1. Kott, Phillip S. & Fetter, Matthew J., 1999. "Using Multi-Phase Sampling to Limit Respondent Burden Across Agriculture Surveys," NASS Research Reports 235075, United States Department of Agriculture, National Agricultural Statistics Service.
    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. Linda J. Young & Lu Chen, 2022. "Using Small Area Estimation to Produce Official Statistics," Stats, MDPI, vol. 5(3), pages 1-17, September.
    2. repec:ags:unassr:235089 is not listed on IDEAS
    3. Lisic Jonathan & Sang Hejian & Zimmer Stephanie & Zhu Zhengyuan, 2018. "Optimal Stratification and Allocation for the June Agricultural Survey," Journal of Official Statistics, Sciendo, vol. 34(1), pages 121-148, March.
    4. Kott, Phillip S., 2001. "Using the Delete-a-Group Jackknife Variance Estimator in NASS Surveys," NASS Research Reports 235089, United States Department of Agriculture, National Agricultural Statistics Service.
    5. R. Benedetti & M. S. Andreano & F. Piersimoni, 2019. "Sample selection when a multivariate set of size measures is available," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(1), pages 1-25, March.

    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. repec:ags:unassr:234380 is not listed on IDEAS

    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:ags:unasrr:234380. 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: AgEcon Search (email available below). General contact details of provider: https://www.nass.usda.gov/ .

    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.