IDEAS home Printed from https://ideas.repec.org/a/vrs/offsta/v34y2018i1p121-148n7.html
   My bibliography  Save this article

Optimal Stratification and Allocation for the June Agricultural Survey

Author

Listed:
  • Lisic Jonathan

    (Cigna, 900 Cottage Grove Rd, Bloomfield, CT 06002, USA)

  • Sang Hejian
  • Zimmer Stephanie

    (Iowa State University, Osborn Dr, Ames, IA 50011 USA)

  • Zhu Zhengyuan

    (Iowa State University, Osborn Dr, Ames, IA 50011 USA)

Abstract

A computational approach to optimal multivariate designs with respect to stratification and allocation is investigated under the assumptions of fixed total allocation, known number of strata, and the availability of administrative data correlated with thevariables of interest under coefficient-of-variation constraints. This approach uses a penalized objective function that is optimized by simulated annealing through exchanging sampling units and sample allocations among strata. Computational speed is improved through the use of a computationally efficient machine learning method such as K-means to create an initial stratification close to the optimal stratification. The numeric stability of the algorithm has been investigated and parallel processing has been employed where appropriate. Results are presented for both simulated data and USDA’s June Agricultural Survey. An R package has also been made available for evaluation.

Suggested Citation

  • 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.
    • Handle: RePEc:vrs:offsta:v:34:y:2018:i:1:p:121-148:n:7
    DOI: 10.1515/jos-2018-0007
    as

    Download full text from publisher

    File URL: https://doi.org/10.1515/jos-2018-0007
    Download Restriction: no
    File URL: https://libkey.io/10.1515/jos-2018-0007?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. & 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.
    2. Barcaroli, Giulio, 2014. "SamplingStrata: An R Package for the Optimization of Stratified Sampling," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i04).
    3. Bruce Hajek, 1988. "Cooling Schedules for Optimal Annealing," Mathematics of Operations Research, INFORMS, vol. 13(2), pages 311-329, May.
    Full references (including those not matched with items on IDEAS)

    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. C. P. Stephens & W. Baritompa, 1998. "Global Optimization Requires Global Information," Journal of Optimization Theory and Applications, Springer, vol. 96(3), pages 575-588, March.
    2. Stoica, R.S. & Gregori, P. & Mateu, J., 2005. "Simulated annealing and object point processes: Tools for analysis of spatial patterns," Stochastic Processes and their Applications, Elsevier, vol. 115(11), pages 1860-1882, November.
    3. George Kapetanios, 2005. "Variable Selection using Non-Standard Optimisation of Information Criteria," Working Papers 533, Queen Mary University of London, School of Economics and Finance.
    4. Souvik Das & Ashwin Aravind & Ashish Cherukuri & Debasish Chatterjee, 2022. "Near-optimal solutions of convex semi-infinite programs via targeted sampling," Annals of Operations Research, Springer, vol. 318(1), pages 129-146, November.
    5. Pirlot, Marc, 1996. "General local search methods," European Journal of Operational Research, Elsevier, vol. 92(3), pages 493-511, August.
    6. Steinhofel, K. & Albrecht, A. & Wong, C. K., 1999. "Two simulated annealing-based heuristics for the job shop scheduling problem," European Journal of Operational Research, Elsevier, vol. 118(3), pages 524-548, November.
    7. Löwe, Matthias, 1997. "On the invariant measure of non-reversible simulated annealing," Statistics & Probability Letters, Elsevier, vol. 36(2), pages 189-193, December.
    8. Miclo, Laurent, 1995. "Remarques sur l'ergodicité des algorithmes de recuit simulé sur un graphe," Stochastic Processes and their Applications, Elsevier, vol. 58(2), pages 329-360, August.
    9. Kapetanios, George, 2006. "Cluster analysis of panel data sets using non-standard optimisation of information criteria," Journal of Economic Dynamics and Control, Elsevier, vol. 30(8), pages 1389-1408, August.
    10. Antonio Jiménez-Martín & Alfonso Mateos & Josefa Z. Hernández, 2021. "Aluminium Parts Casting Scheduling Based on Simulated Annealing," Mathematics, MDPI, vol. 9(7), pages 1-18, March.
    11. Van Buer, Michael G. & Woodruff, David L. & Olson, Rick T., 1999. "Solving the medium newspaper production/distribution problem," European Journal of Operational Research, Elsevier, vol. 115(2), pages 237-253, June.
    12. Zhang Lihao & Ye Zeyang & Deng Yuefan, 2019. "Parallel MCMC methods for global optimization," Monte Carlo Methods and Applications, De Gruyter, vol. 25(3), pages 227-237, September.
    13. Yiyo Kuo, 2014. "Design method using hybrid of line-type and circular-type routes for transit network system optimization," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 22(2), pages 600-613, July.
    14. Broekmeulen, Rob A. C. M. & van Weert, Arjen & Saedt, Anton P. H., 2002. "Comparing three alternative optimisation methods for the treatment planning of bulbs," Agricultural Systems, Elsevier, vol. 72(1), pages 59-71, April.
    15. F. R. B. Cruz & A. R. Duarte & G. L. Souza, 2018. "Multi-objective performance improvements of general finite single-server queueing networks," Journal of Heuristics, Springer, vol. 24(5), pages 757-781, October.
    16. Rodriguez-Tello, Eduardo & Hao, Jin-Kao & Torres-Jimenez, Jose, 2008. "An improved simulated annealing algorithm for bandwidth minimization," European Journal of Operational Research, Elsevier, vol. 185(3), pages 1319-1335, March.
    17. Doole, Graeme J., 2007. "A primer on implementing compressed simulated annealing for the optimisation of a constrained simulation model in Microsoft Excel," Working Papers 7420, University of Western Australia, School of Agricultural and Resource Economics.
    18. Sam Hui & Eric Bradlow, 2012. "Bayesian multi-resolution spatial analysis with applications to marketing," Quantitative Marketing and Economics (QME), Springer, vol. 10(4), pages 419-452, December.
    19. Zhao, Fang & Zeng, Xiaogang, 2008. "Optimization of transit route network, vehicle headways and timetables for large-scale transit networks," European Journal of Operational Research, Elsevier, vol. 186(2), pages 841-855, April.
    20. Gabriel M. Portal & Marcus Ritt & Leonardo M. Borba & Luciana S. Buriol, 2016. "Simulated annealing for the machine reassignment problem," Annals of Operations Research, Springer, vol. 242(1), pages 93-114, July.

    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:vrs:offsta:v:34:y:2018:i:1:p:121-148:n:7. 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: Peter Golla (email available below). General contact details of provider: https://www.sciendo.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.