Article
Health Care Sciences & Services
Chandraketu Singh, Mustafa Kamal, Garib Nath Singh, Jong-Min Kim
Summary: The study proposes new efficient scrambled response models for estimating the population mean of quantitative sensitive characteristics using additive and multiplicative techniques. The efficacy of the models is examined using degree of privacy protection and unified measure approaches, with results showing higher efficiency and greater privacy protection compared to existing models. When applied on successive occasions, the proposed models consistently outperform competitors, indicating their potential as the best alternative for dealing with changing sensitive characteristics over time.
RISK MANAGEMENT AND HEALTHCARE POLICY
(2021)
Article
Computer Science, Artificial Intelligence
Rixuan Qiu, Xiong Liu, Rong Huang, Fuyong Zheng, Liang Liang, Yuancheng Li
Summary: In this paper, a privacy protection mechanism based on differential privacy is proposed to protect the release of data in V2G networks. The use of a variable sliding window helps to improve the utility of the data and allocate privacy budget reasonably. Additionally, experimental analysis shows that the proposed method is superior to existing schemes and enhances data utility.
PEERJ COMPUTER SCIENCE
(2021)
Article
Multidisciplinary Sciences
Nitesh Kumar Adichwal, Abdullah Ali H. Ahmadini, Yashpal Singh Raghav, Rajesh Singh, Irfan Ali
Summary: This paper proposes a new estimator for estimating the general parameter t((a,b)) using auxiliary information in simple random sampling without replacement (SRSWOR). The efficiency of the suggested estimator and existing estimators is analyzed and the proposed estimator is found to be more effective.
JOURNAL OF KING SAUD UNIVERSITY SCIENCE
(2022)
Article
Engineering, Multidisciplinary
Muhammad Wasim Amir, Zeeshan Raza, Zameer Abbas, Hafiz Zafar Nazir, Noureen Akhtar, Muhammad Riaz, Muhammad Abid
Summary: Control chart is the most useful tool in monitoring manufacturing processes, and its sensitivity can be improved by introducing auxiliary information. The AB-MA control chart designed in this study outperforms competitors in detecting small and medium changes in the process location parameter.
QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL
(2021)
Article
Mathematics, Applied
Saman Hanif Shahbaz, Aisha Fayomi, Muhammad Qaiser Shahbaz
Summary: This paper proposes some estimators for the estimation of general population parameters. The estimators are for single-phase and two-phase sampling using information of single and multiple auxiliary variables. The bias and mean square errors of the proposed estimators are derived and compared with existing estimators for mean and variance. Specific cases of the proposed estimators are discussed. Simulation and numerical study are conducted to evaluate the performance of the proposed estimators.
Article
Computer Science, Interdisciplinary Applications
Muhammad Wasim Amir, Mishal Rani, Zameer Abbas, Hafiz Zafar Nazir, Muhammad Riaz, Noureen Akhtar
Summary: The proposed ADMA control chart based on auxiliary information is effective in monitoring process mean. The run-length profiles of the ADMA control chart are calculated using Monto Carlo simulation, showing its superior performance compared to memory-type counterparts. Numerical simulation study demonstrates the uniformly better performance of the ADMA chart structure in terms of average run length and other characteristics.
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
(2021)
Article
Multidisciplinary Sciences
Hareem Abbasi, Muhammad Hanif, Usman Shahzad, Walid Emam, Yusra Tashkandy, Soofia Iftikhar, Shabnam Shahzadi
Summary: Outliers are observations that deviate significantly from the rest of the dataset. Due to their asymmetry, estimating the cumulative distribution function (CDF) is not extensively explored for such observations. In this article, we propose a calibration methodology with auxiliary information to modify traditional stratification weight, which allows us to obtain efficient estimates of the CDF using robust measures like mid-range and tri-mean under different distance functions. A simulation study evaluates the performance of the proposed estimators compared to existing ones using real-life asymmetric datasets.
Article
Statistics & Probability
Ghulam Narjis, Javid Shabbir
Summary: This paper proposes a new scrambled randomized response (SRR) model for estimating the population mean of a sensitive variable under simple random sampling with replacement (SRSWR), and explores its utility in successive sampling. The study finds that the proposed SRR model is superior to the traditional additive model under SRSWR and successive sampling. Additionally, a composite class of estimators is proposed, which is shown to be more efficient than classical ratio and exponential ratio type estimators respectively under optimum conditions.
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
(2023)
Article
Economics
Zongwu Cai, Haiqiang Chen, Xiaosai Liao
Summary: This paper proposes a novel approach to offer a robust inferential theory across all types of persistent regressors in a predictive quantile regression model. The approach involves estimating a quantile regression with an auxiliary regressor and constructing a weighted estimator using the estimated coefficients of the original predictor and the auxiliary regressor. The approach demonstrates good properties in terms of reaching the optimal power under different predictor conditions and characterizing mixed persistency degrees in multiple regressions.
JOURNAL OF ECONOMETRICS
(2023)
Article
Mathematics, Applied
Muhammad Amin, Hajra Ashraf, Hassan S. Bakouch, Najla Qarmalah
Summary: This study proposes the James Stein Estimator for the beta regression model to address the issue of inaccurate estimation with correlated explanatory variables. Through simulation experiments and real-life applications, it is found that the proposed estimator outperforms other competitive estimators in estimating the parameters of the beta regression model.
Article
Business
Lauren Labrecque, Ereni Markos, Kunal Swani, Priscilla Pena
Summary: The research shows that stress and perceptions of social contract violation significantly impact the outcomes of data breaches, and different data types also affect consumer coping behaviors. Taking actions could help reduce negative consumer responses.
JOURNAL OF BUSINESS RESEARCH
(2021)
Article
Mathematics, Applied
Muhammad Azeem
Summary: This paper introduces the novel idea of using the exponential function of scrambling variable in quantitative randomized response models. Two new quantitative randomized response models based on exponential scrambling variable are proposed. It is found that the new randomized response models are more efficient than the existing ones. The mathematical properties of the mean estimator of the sensitive variable and the measures of privacy protection and efficiency are discussed.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Meteorology & Atmospheric Sciences
Maria Lorena Orellana-Samaniego, Daniela Ballari, Pablo Guzman, Jesus Efren Ospina
Summary: This study estimated the spatial distribution of monthly air temperature in the Paute river basin using statistical and geostatistical methods, showing that random forest regression outperformed linear regression, and the inclusion of auxiliary variables improved estimation accuracy. However, the application of regression kriging was limited by spatial autocorrelation in the regression model residuals in less than 50% of the months, although it improved estimation performance in the months with spatial autocorrelation.
THEORETICAL AND APPLIED CLIMATOLOGY
(2021)
Article
Computer Science, Interdisciplinary Applications
Iram Saleem, Aamir Sanullah, Javid Shabbir, Husna Sadaf, Riffat Jabeen
Summary: A generalized scrambled randomized response model is developed to balance efficiency and privacy protection, and the simulation and empirical results demonstrate that the proposed estimators are more efficient than the existing ones.
JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION
(2022)
Article
Automation & Control Systems
Shi Liang, James Lam, Hong Lin
Summary: This article focuses on solving the state estimation problems for a system with protecting user privacy. A privacy-preserving mechanism (PPM) is proposed to prevent the disclosure or inference of user's action results, and a computationally efficient suboptimal estimator (SE) is designed to satisfy both privacy protection and estimation performance requirements.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
