Results 11 to 20 of about 645,422 (275)
Robust Lavallee-Hidiroglou stratified sampling strategy
Survey Research Methods, 2012 There are several reasons why robust regression techniques are useful tools in sampling design. First of all, when stratified samples are considered, one needs to deal with three main issues: the sample size, the strata bounds determination and the ...
Maria Caterina Bramati
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Federated learning based on stratified sampling and regularization
Complex & Intelligent Systems, 2022 Federated learning (FL) is a new distributed learning framework that is different from traditional distributed machine learning: (1) differences in communication, computing, and storage performance among devices (device heterogeneity), (2) differences in
Chenyang Lu +4 more
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Estimation of Sensitive Attributes Using a Stratified Kuk Randomization Device
Revista Colombiana de Estadística, 2017 This paper suggests a stratified Kuk model to estimate the proportion of sensitive attributes of a population composed by a number of strata; this is undertaken by applying stratified sampling to the adjusted Kuk model.
LEE GI-SUNG +3 more
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Calibration-Based Mean Estimators under Stratified Median Ranked Set Sampling
Mathematics, 2023 Using auxiliary information, the calibration approach modifies the original design weights to enhance the mean estimates. This paper initially proposes two families of estimators based on an adaptation of the estimators presented by recent researchers ...
Usman Shahzad +4 more
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Functional quantization-based stratified sampling methods [PDF]
, 2010 In this article, we propose several quantization-based stratified sampling methods to reduce the variance of a Monte Carlo simulation. Theoretical aspects of stratification lead to a strong link between optimal quadratic quantization and the variance ...
Corlay, Sylvain, Pagès, Gilles
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Resolving the Raven Paradox: Simple Random Sampling, Stratified Random Sampling, and Inference to the Best Explanation [PDF]
, 2021 Simple random sampling resolutions of the raven paradox relevantly diverge from scientific practice. We develop a stratified random sampling model, yielding a better fit and apparently rehabilitating simple random sampling as a legitimate idealization.
Ward, Barry
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Stratified Feature Sampling for Semi-Supervised Ensemble Clustering
IEEE Access, 2019 Ensemble Clustering (EC), which seeks to generate a consensus clustering by integrating multiple base clusterings, has attracted increasing attentions.
Jialin Tian, Yazhou Ren, Xiang Cheng
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Sampling plan and methodological aspects: a household healthcare survey in Piauí
Revista de Saúde Pública, 2021 OBJECTIVE To describe the methodological aspects of the Piauí home healthcare survey (ISAD-PI) and assess the relation between sampling plan, precision, and design effects, assuming that population health surveys are relevant instruments for health ...
Lays Arnaud Rosal Lopes Rodrigues +13 more
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Journal of Statistical Theory and Applications (JSTA), 2019 This article proposes some estimators based on an adaptation of the estimators developed by Bahl and Tuteja [1], Diana [2], Koyuncu and Kadilar [3], Koyuncu and Kadilar [4], Shabbir and Gupta [5], and Koyuncu [6] utilizing available supplementry ...
Usman Shahzad +3 more
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An Inverse-Occurrence Sampling Approach for Urban Flood Susceptibility Mapping
Remote Sensing, 2023 Data-driven flood susceptibility modeling is an efficient way to map the spatial distribution of flood likelihood. The quality of the flood susceptibility model relies on the learning technique and the data used for learning.
Changpeng Wang +5 more
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