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Articles by Javid Shabbir
On the estimation of population mode in time-scaled surveys using ranked auxiliary information
Advanced search Communications in Statistics - Simulation and Computation Latest Articles Submit an article Journal homepage Full Article Figures & data References Citations Metrics Reprints & Permissions Read this article /doi/full/10.1080/03610918.2026.2719880?needAccess=true Abstract The existing mode estimators are traditionally based on one-time sample surveys, which may adversely affect the estimates due to measurement errors arising during the interviewing process.
Novel randomized response method for mean estimation using exponential estimators
Advanced search Communications in Statistics - Theory and Methods Latest Articles Submit an article Journal homepage Full Article Figures & data References Citations Metrics Reprints & Permissions Read this article /doi/full/10.1080/03610926.2025.2607440?needAccess=true Abstract. In applied research, the objective of the study often involves topics of a sensitive nature.
On use of adaptive cluster sampling for variance estimation
Advanced search Journal of Applied Statistics Latest Articles Submit an article Journal homepage Full Article Figures & data References Citations Metrics Reprints & Permissions Read this article /doi/full/10.1080/02664763.2025.2460072?needAccess=true Abstract Adaptive cluster sampling is particularly helpful whenever the target population is unique, dispersed unevenly, concealed or difficult to find.
A New Difference-Cum-Exponential Type Estimator of Finite Population Mean in Simple Random Sampling
Ayuda Buscar en la ayuda Buscar en la ayuda A New Difference-Cum-Exponential Type Estimator of Finite Population Mean in Simple Random Sampling JAVID SHABBIR [1] ; ABDUL HAQ [1] ; SAT GUPTA [2] [1] Quaid-I-Azam University Department of Statistics [2] The University of North Carolina at Greensboro Department of Mathematics and Statistics Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 37, Nº. 1, 2014, págs.
A Note on Generalized Exponential Type Estimator for Population Variance in Survey Sampling
Ayuda Buscar en la ayuda Buscar en la ayuda A Note on Generalized Exponential Type Estimator for Population Variance in Survey Sampling JAVID SHABBIR [1] ; SAT GUPTA [2] [1] Quaid-i-Azam University Department of Statistics [2] The University of North Carolina at Greensboro Department of Mathematics and Statistics Localización: Revista Colombiana de Estadística, ISSN-e 2389-8976, ISSN 0120-1751, Vol. 38, Nº. 2, 2015, págs.
A comparative study of randomized response techniques using separate and combined metrics of efficiency and privacy
Loading metrics Open Access Peer-reviewed Research Article Citation: Azeem M, Shabbir J, Salahuddin N, Hussain S, Ijaz M (2023) A comparative study of randomized response techniques using separate and combined metrics of efficiency and privacy. PLoS ONE 18(10): e0293628.
Ratio-Type Estimator for Estimating the Neutrosophic Population Mean in Simple Random Sampling under Intuitionistic Fuzzy Cost Function
1. Introduction Survey sampling is the most practical and cost-effective approach for collecting data for research or estimating population means for making decisions. The validity and practicality of these judgments are dependent on the accuracy and precision of estimates, which are significantly affected by two important decisions made during the planning stage of a simple random sampling scheme.
Estimation of finite population mean for a sensitive variable using dual auxiliary information in the presence of measurement errors
Loading metrics Open Access Peer-reviewed Research Article Erum Zahid , Javid Shabbir Erum Zahid, Javid Shabbir Published: February 11, 2019 https://doi.org/10.1371/journal.pone.0212111 Figures Abstract 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. This estimator accounts the auxiliary information as well as the ranks of the auxiliary variable.
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