Results 11 to 20 of about 265,026 (252)
Constructing efficient strata boundaries in stratified sampling using survey cost [PDF]
For maximum precision in population parameter estimation under the Stratified sampling design, the optimum strata boundaries (OSB) could be constructed based on a continuous study variable rather than a set of categorical variables.
Karuna G. Reddy, M.G.M. Khan
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Federated learning based on stratified sampling and regularization
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
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
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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Stratified Feature Sampling for Semi-Supervised Ensemble Clustering
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
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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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
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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SAMPLING METHODS AND NUMBER OF ROUNDWOODS FOR DETERMINING THE MOISTURE CONTENT
This study had the objective of comparing two methodologies of sampling, Simple Random Sampling (ACS) and Stratified Random Sampling (ACE) to determine the optimum number of roundwood samples to obtain the moisture content of the population.
Danilo Barros Donato +5 more
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Assessing Antithetic Sampling for Approximating Shapley, Banzhaf, and Owen Values
Computing Shapley values for large cooperative games is an NP-hard problem. For practical applications, stochastic approximation via permutation sampling is widely used. In the context of machine learning applications of the Shapley value, the concept of
Jochen Staudacher, Tim Pollmann
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