Browsing by Author "Pokhrel, R"

Now showing 1 - 4 of 4
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    Design based synthetic imputation methods for domain mean
    (2024) Bhushan, S; Kumar, A; Pokhrel, R
    In real life, situations may arise when the available data are insufcient to provide accurate estimates for the domain, the small area estimation (SAE) technique has been used to get accurate estimates for the variable under study. The problem of missing data is a serious problem that has an impact on sample surveys, but small area estimates are especially prone to it. This paper is a basic efort that suggests design based synthetic imputation methods for the domain mean estimation using simple random sampling in order to address the issue of missing data under SAE. The expression of the mean square error for the proposed imputation methods are obtained up to frst order approximation. The efciency conditions are determined and a thorough simulation study is carried out using artifcially generated data sets. An application is included with real data that further supports this study.
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    Enhanced direct and synthetic estimators for domain mean with simulation and applications
    (2024-07) Kumar, A; Bhushan, S; Pokhrel, R; Emam, W; Tashkandy, Y; Khan, M
    This article considers the issue of domain mean estimation utilizing bivariate auxiliary information based enhanced direct and synthetic logarithmic type estimators under simple random sampling (SRS). The expressions of mean square error (MSE) of the proposed estimators are provided to the 1𝑠𝑡 order approximation. The efficiency criteria are derived to exhibit the dominance of the proposed estimators. To exemplify the theoretical results, a simulation study is conducted on a hypothetically drawn trivariate normal population from 𝑅 programming language. Some applications of the suggested methods are also provided by analyzing the actual data from the municipalities of Sweden and acreage of paddy crop in the Mohanlal Ganj tehsil of the Indian state of Uttar Pradesh. The findings of the simulation and real data application exhibit that the proposed direct and synthetic logarithmic estimators dominate the conventional direct and synthetic mean, ratio, and logarithmic estimators in terms of least MSE and highest percent relative efficiency.
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    Logarithmic Type Direct and Synthetic Estimators for Domain Mean Using Simple Random Sampling
    (2024-01) Bhushan, S; Kumar, A; Pokhrel, R
    In this article, we propose logarithmic type direct and synthetic estima tors for the estimation of domain mean under simple random sampling. The properties such as bias and mean square error of the proposed direct and synthetic estimators are obtained up to rst order approximation. The e - ciency conditions are obtained under which the proposed direct and synthetic estimators outperform their conventional counterparts. The performance of the proposed direct and synthetic estimators is examined with the help of comprehensive computational study using real and arti cially drawn popu lations. Some appropriate suggestions are also provided to the surveyors.
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    Small area estimation using design based direct and synthetic logarithmic estimators
    (2024-05) Kumar, A; Bhushan, S; Pokhrel, R; Emam, W
    In this article, we propose some direct and synthetic logarithmic estimators for estimating the domain mean of small area based on a simple random sampling design. The mean square error expressions of the proposed direct and synthetic estimators are obtained to first order approximation. The efficiency conditions are obtained under which the proposed direct and synthetic estimators dominate their conventional aspirants. The performances of the suggested direct and synthetic logarithmic estimators are examined by a comprehensive simulation study carried out on some artificially drawn symmetric and asymmetric populations. Furthermore, a real data application of the suggested methods is also provided as a case study using the paddy crop acreage data for small domains, where small domains are the revenue inspector circles (RIC) in Mohanlalganj tehsil, Uttar Pradesh, India.