Results 1 to 10 of about 60,047 (288)
On use of adaptive cluster sampling for variance estimation [PDF]
Journal of Applied StatisticsAdaptive cluster sampling is particularly helpful whenever the target population is unique, dispersed unevenly, concealed or difficult to find. In the current investigation, under an adaptive cluster sampling approach, we propose a ratio-product-logarithmic type estimator employing a single auxiliary variable for the estimation of finite population ...
Shameem Alam, Javid Shabbir
exaly +4 more sources
Precision enhancement in variance estimation for complex environmental populations using adaptive cluster sampling [PDF]
HeliyonEstimating dispersion in populations that are extremely rare, hidden, geographically clustered, and hard to access is a well-known challenge. Conventional sampling approaches tend to overestimate the variance, even though it should be genuinely reduced ...
Muhammad Nouman Qureshi +6 more
doaj +2 more sources
Cluster Target Tracking Based on Multi-Sensor Adaptive GLMB Filter [PDF]
SensorsIn complex detection environments, unknown detection probability and clutter rate hinder accurate tracking of cluster targets. To address this issue, this paper proposes a novel multi-sensor adaptive generalized labeled multi-Bernoulli (MS-AGLMB) filter.
Zheng Zhang, Daozhi Wei, Xirui Xue
doaj +2 more sources
Generalized robust regression techniques and adaptive cluster sampling for efficient estimation of population mean in case of rare and clustered populations [PDF]
Scientific ReportsSituations when field researchers are tempted to deviate from preselected sampling plan and to include nearby or related units in sample, then adaptive cluster sampling (ACS) offers a nearly completion solution.
Mir Subzar +6 more
doaj +2 more sources
PLoS ONE, 2021 Sampling rare and clustered populations is challenging because of the effort required to find rare units. Heuristically, a practitioner would prefer to discontinue sampling in areas where rare units of interest are apparently extremely sparse or absent ...
Mohammad Salehi, David R Smith
doaj +1 more source
Arithmetic, 2023 This research aims to determine the effect of the CPS learning model on mathematical adaptive reasoning ability in terms of students' entrepreneurial character.
Komarudin Komarudin +4 more
doaj +1 more source
Journal of Forest Science, 2012 Based on two species of Coastal Mangrove in Hainan of China, Sonneratia Apetala Buch-Ham and Sonneratia caseoli, we estimated the density of the two species to evaluate the efficiency of adaptive cluster sampling (ACS), simple random sampling (SRS) and ...
Y. Lei, J. Shi, T. Zhao
doaj +1 more source
Fast and interpretable consensus clustering via minipatch learning.
PLoS Computational Biology, 2022 Consensus clustering has been widely used in bioinformatics and other applications to improve the accuracy, stability and reliability of clustering results.
Luqin Gan, Genevera I Allen
doaj +1 more source
On two-stage adaptive cluster sampling to assess pest density
浙江大学学报. 农业与生命科学版, 2000 The adaptive cluster sampling introduced by Thompson is a powerful method for a survey of a population which is highly clumped with clumps widely separated.
ZHANG Nan-song +2 more
doaj +1 more source
DisSAGD: A Distributed Parameter Update Scheme Based on Variance Reduction
Sensors, 2021 Machine learning models often converge slowly and are unstable due to the significant variance of random data when using a sample estimate gradient in SGD.
Haijie Pan, Lirong Zheng
doaj +1 more source