An efficient estimator of population variance of a sensitive variable with a new randomized response technique [PDF]
HeliyonIn sampling theory, a majority of the available estimators of population variance are designed for use with non-sensitive variables only. Such estimators cannot perform efficiently when the variable of interest is of sensitive nature, such as use of ...
Muhammad Azeem +4 more
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Efficient estimation of population variance of a sensitive variable using a new scrambling response model [PDF]
Scientific Reports, 2023 This study introduces a pioneering scrambling response model tailored for handling sensitive variables. Subsequently, a generalized estimator for variance estimation, relying on two auxiliary information sources, is developed following this novel model ...
Iram Saleem +4 more
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A generalized class of estimators for sensitive variable in the presence of measurement error and non-response. [PDF]
PLoS ONE, 2022 In this paper, a general class of estimators is proposed for estimating the finite population mean for sensitive variable, in the presence of measurement error and non-response in simple random sampling.
Erum Zahid +4 more
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Inversion model of soil salinity in alfalfa covered farmland based on sensitive variable selection and machine learning algorithms [PDF]
PeerJPurpose Timely and accurate monitoring of soil salinity content (SSC) is essential for precise irrigation management of large-scale farmland. Uncrewed aerial vehicle (UAV) low-altitude remote sensing with high spatial and temporal resolution provides a ...
Hong Ma +5 more
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Variable Protease-Sensitive Prionopathy Transmission to Bank Voles [PDF]
Emerging Infectious Diseases, 2019 Variably protease-sensitive prionopathy (VPSPr), a recently described human sporadic prion disease, features a protease-resistant, disease-related prion protein (resPrPD) displaying 5 fragments reminiscent of Gerstmann-Sträussler-Scheinker disease ...
Romolo Nonno +12 more
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Cost-Sensitive Variable Selection for Multi-Class Imbalanced Datasets Using Bayesian Networks
Mathematics, 2021 Multi-class classification in imbalanced datasets is a challenging problem. In these cases, common validation metrics (such as accuracy or recall) are often not suitable.
Darío Ramos-López, Ana D. Maldonado
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Estimation of finite population mean for a sensitive variable using dual auxiliary information in the presence of measurement errors. [PDF]
PLoS One, 2019 In this study, we propose a new improved estimator of population mean for the sensitive variable in the presence of measurement error under simple and stratified random sampling.
Zahid E, Shabbir J.
europepmc +2 more sources
Calibrated-Two Optional Randomized Response Techniques (C-TORRT) for the estimation of quantitative sensitive variable information. [PDF]
PLoS ONEAccurate estimation of sensitive quantitative variables remains a challenge in survey research due to respondents' reluctance to disclose truthful information. While existing randomized response techniques (RRT) offer privacy protection, many suffer from
Mojeed Abiodun Yunusa +4 more
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Improved estimator for the estimation of sensitive variable using ORRT models
Research in StatisticsIn this study, we concern with the improved estimation of sensitive variable when there is non-response and measurement error on sensitive variable but the auxiliary variable is non sensitive in nature.
Sunil Kumar, Chanda Rani
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Applied Sciences, 2019 Multivariate time series are often accompanied with missing values, especially in clinical time series, which usually contain more than 80% of missing data, and the missing rates between different variables vary widely. However, few studies address these
Qianting Li, Yong Xu
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