Results 21 to 30 of about 103 (99)

Detection of multivariate outliers in business survey data with incomplete information

, 2010
Multivariate outlier detection, Robust statistics, Missing values, 62G35, 62D05, 62H99,
Valentin Todorov, Filzmoser, Peter, Matthias Templ, Todorov, Valentin, Templ, Matthias, Peter Filzmoser   +5 more
core   +1 more source

Empirical Bayes and Bootstrap Inference for Multicomponent Stress–Strength Reliability Under Ordered Ranked Set Sampling

Journal of Mathematics, Volume 2026, Issue 1, 2026.
This paper develops a unified inferential framework for multicomponent stress–strength reliability when the number of active components is stochastic rather than fixed. The system size is modeled by a left‐truncated binomial distribution, while strength and stress information are collected through two complementary designs: ordered ranked set sampling ...
Haidy A. Newer, Bader S. Alanazi, Smritijit Sen   +2 more
wiley   +1 more source

A NEW FAMILY OF ESTIMATORS OF THE POPULATION VARIANCE USING INFORMATION ON POPULATION VARIANCE OF AUXILIARY VARIABLE IN SAMPLE SURVEYS [PDF]

, 2016
This paper proposes a family of estimators of population variance 2 y S of the study variable y in the presence of known population variance 2 x S of the auxiliary variable x.
P. Singh, Housila, Housila P. Singh, Pal, Surya K., Singh, Housila P., K. Pal, Surya, Surya K. Pal   +5 more
core   +1 more source

Global-Local Priors for Spatial Small Area Estimation

, 2023
Small area estimation is gaining increasing popularity among survey statisticians. Since the direct estimates of small areas usually have large standard errors, model-based approaches are often adopted to borrow strength across areas.
Malay Ghosh, Xueying Tang, Tang, Xueying, Ghosh, Malay   +3 more
core   +1 more source

Parametric Inference for a Multicomponent Stress–Strength Reliability Model With Kumaraswamy Distribution Under Ordered Ranked Set Sampling

Journal of Mathematics, Volume 2026, Issue 1, 2026.
Assessing reliability in systems with dual stress constraints needs a flexible model and effective sampling methods. A framework using the Kumaraswamy distribution is set up for multicomponent stress and strength systems. Data collection is done through ordered ranked set sampling, leveraging the unified theory of generalized order statistics to ...
Haidy A. Newer, Bader S. Alanazi, Smritijit Sen   +2 more
wiley   +1 more source

Optimizing population mean estimation using regression and factor type estimators in the presence of non-response

Franklin Open
This paper addresses the problem of estimating the population mean of the study variable, Y, in the presence of non-response. To address this, we incorporated two additional variables, X and Z, as auxiliary variables.
Ashok K. Jaiswal, M.K. Pandey, G.N. Singh   +2 more
doaj   +1 more source

Bootstrap for estimating the MSE of the Spatial EBLUP

, 2009
Spatial correlation, Simultaneously autoregressive process, Small area estimation, Parametric bootstrap, Non-parametric bootstrap, 62D05, 62J05,
SALVATI, NICOLA, PRATESI, MONICA, Isabel Molina, Nicola Salvati, Monica Pratesi, MOLINA I   +5 more
core   +1 more source

A novel statistical framework: Theoretical foundations: Properties, and application in vocational education and radiation sciences

Journal of Radiation Research and Applied Sciences
Proper estimation of population variation is very important for statistical inference, quality measurement, and decision-making in various fields of science.
Yijun Shen, Mohamed Kayid, Ghadah A. Alomani   +2 more
doaj   +1 more source

The enhanced population parameter estimation under the umbrella of random sampling: Practical evidence from transmission system, accounting and radiation sciences

Journal of Radiation Research and Applied Sciences
Estimating variance is basic problem in survey sampling because variance measure dispersion, heterogeneity, and the reliability of statistical inference.
Lingxiao Qiao, Shanzhi Xu, Fang Li, Iman Babiker, Diaa S. Metwally, Mona Almutairi   +5 more
doaj   +1 more source

Distinguishability of causal structures under latent confounding and selection

Journal of Causal Inference
Statistical relationships in observed data can arise for several different reasons: the observed variables may be causally related, they may share a latent common cause, or there may be selection bias.
Carey Ryan, Maciel Ansanelli Marina, Wolfe Elie, Evans Robin J.   +3 more
doaj   +1 more source