{
  "abstract": "In simple random sampling without replacement (SRSWOR), auxiliary information is an important component for improving the precision of estimators of finite population means. Although a few estimators have been developed to combine dual auxiliary information using a ratio-cum-exponential structure, most estimators rely on a single auxiliary variable, either through ratio, product, or regression structures. This study presents a new ratio/cu-exponential estimator for estimation of the finite population mean by combining two auxiliary variables in an optimized exponential structure. We determine the bias and mean squared error (MSE) of the proposed estimator using a first-order approximation method, and we determine the optimal values of the characterizing constants analytically. We formulate conditions for theoretical efficiency to compare the proposed estimator with conventional estimators such as the sample mean, ratio, product, regression, exponential, and existing dual auxiliary estimators. We also use a real dataset from a radiation monitoring and economic management application to evaluate the proposed estimator’s performance in terms of MSE and PRE. The results show that the proposed estimator has uniformly lower MSE and PRE than the other estimators across various correlation structures and population characteristics. The proposed ratio-cum-exponential estimator has been verified to be a powerful and efficient method for estimating finite population means in various scientific, physical, and socio-economic settings.",
  "abstract_shown": true,
  "affiliations": [
    "School of Economics and Management, Jiujiang Polytechnic University of Science and Technology, Jiujiang 332020, Jiangxi, China; Corresponding author.",
    "School of Architectural and Hydraulic Engineering, Jiujiang Polytechnic, University of Science and Technology, Jiujiang 332020, Jiangxi, China",
    "Department of Mathematical Science, College of Science, Princess Nourah bint Abdulrahman University, P.O. Box 84428, Riyadh 11671, Saudi Arabia",
    "Department of Mathematics, College of Science, Qassim University, Buraydah 51452, Saudi Arabia",
    "Department of Operations and Management Research, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, Egypt"
  ],
  "article_type": null,
  "arxiv": null,
  "author_total": 6,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Aiting Cai"
    },
    {
      "affs": [
        1
      ],
      "name": "Jingwen Li"
    },
    {
      "affs": [
        2
      ],
      "name": "Shahah Almutairi"
    },
    {
      "affs": [
        3
      ],
      "name": "Mona Almutairi"
    },
    {
      "affs": [
        3
      ],
      "name": "Alhanouf Alburaikan"
    },
    {
      "affs": [
        4
      ],
      "name": "Hamiden Abd El-Wahed Khalifa"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/91ht8jhwh8g28.bib",
  "cited_by": 0,
  "doi": "10.1016/j.jrras.2026.102746",
  "fulltext_url": "http://www.sciencedirect.com/science/article/pii/S1687850726005893",
  "id": "91ht8jhwh8g28",
  "issns": [
    "2314-7164",
    "1687-8507"
  ],
  "landing_url": "https://doi.org/10.1016/j.jrras.2026.102746",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
  "licence_source": "journal",
  "licence_url": "https://creativecommons.org/licenses/by/4.0/",
  "metadata_licence": null,
  "native_subjects": [
    [
      "lcc",
      "R895-920"
    ],
    [
      "lcc",
      "TK9001-9401"
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      "openalex",
      "2613|Survey Sampling and Estimation Techniques"
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  "pdf_url": "https://www.sciencedirect.com/science/article/pii/S1687850726005893/pdf",
  "pmcid": null,
  "pmid": null,
  "published": "2026-10-30",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/91ht8jhwh8g28.ris",
  "sources": [
    {
      "first_seen": "2026-10-30T13:44:36Z",
      "native_id": "c98d451cac0c4c968dc64b1347723de2",
      "source": "doaj",
      "url": "https://doi.org/10.1016/j.jrras.2026.102746"
    }
  ],
  "subjects": [
    {
      "field": "mathematics",
      "origin": "openalex:2613|Survey Sampling and Estimation Techniques",
      "subfield": "statistics"
    }
  ],
  "title": "An improved ratio-cum-exponential estimator for finite population mean with properties: Applications to radiation monitoring and economic management data",
  "title_text": "An improved ratio-cum-exponential estimator for finite population mean with properties: Applications to radiation monitoring and economic management data",
  "type": "peer-reviewed",
  "updated_at": "2026-10-30T13:44:36Z",
  "url": "https://research.draconitic.com/paper/91ht8jhwh8g28",
  "venue": "Journal of Radiation Research and Applied Sciences",
  "versions": []
}