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Problem of Compromise Allocation in Multivariate Stratified Sampling Using Intuitionistic Fuzzy Programming

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Abstract

The investigators always have difficulty selecting a sample for the practical use of the stratified random sampling, such that the precision of the finite population under cost constraints is optimized significantly. Identifying stratum boundaries in stratified sample design also includes an essential recurrent challenge in the sampling process. This study presents a realistic way to stratify the population observation based on compromise analysis. The problem is formulated as a deterministic multivariate stratified sampling optimization model with integer variables and is solved by intuitionistic fuzzy programming. Computational studies using two instances demonstrate the optimization of variances inside the strata, therefore considerably reducing accompanying standard errors. Since the suggested model seeks to minimize variances, it can be applied, for example, microeconomic simulation studies, in which an accurate sample is crucial.

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Change history

  • 29 June 2022

    The original version is updated due to the missing of word "Institute" in the affiliation 1.

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Author information

Authors and Affiliations

  1. Department of Decision Sciences, Jaipuria Institute of Management, Jaipur, India

    Srikant Gupta

  2. Department of Statistics and Operations Research, Aligarh Muslim University, Aligarh, UP, India

    Ahteshamul Haq

  3. Department of Statistics, School of Physical and Decision Sciences, Babasaheb Bhimrao Ambedkar University, Lucknow, India

    Rahul Varshney

Authors
  1. Srikant Gupta
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  2. Ahteshamul Haq
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  3. Rahul Varshney
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Correspondence to Srikant Gupta.

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C83, C61.

Ethical statements

I hereby declare that this manuscript is the result of my independent creation under the reviewers’ comments. Except for the quoted contents, this manuscript does not contain any research achievements that have been published or written by other individuals or groups. I am the only author of this manuscript. The legal responsibility of this statement shall be borne by me.

Author contributions

Conceptualization: Srikant Gupta, Ahteshamul Haq, Rahul Varshney; Data curation: Srikant Gupta, Ahteshamul Haq; Formal analysis: Ahteshamul Haq, Rahul Varshney; Investigation: Srikant Gupta, Ahteshamul Haq; Methodology: Srikant Gupta, Rahul Varshney; Project administration: Srikant Gupta, Rahul Varshney; Supervision: Srikant Gupta, Ahteshamul Haq; Validation: Srikant Gupta, Ahteshamul Haq; Visualization: Srikant Gupta, Ahteshamul Haq, Rahul Varshney; Writing – original draft: Srikant Gupta, Ahteshamul Haq, Rahul Varshney; Writing – review & editing: Srikant Gupta, Ahteshamul Haq, Rahul Varshney.

Conflict of interest

I declare that there is no conflict of interest in the publication of this article, and that there is no conflict of interest with any other author or institution for the publication of this article.

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Gupta, S., Haq, A. & Varshney, R. Problem of Compromise Allocation in Multivariate Stratified Sampling Using Intuitionistic Fuzzy Programming. Ann. Data. Sci. 11, 425–444 (2024). https://doi.org/10.1007/s40745-022-00410-y

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