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Mingfeng Huang, Jianping Sun, Kang Cai and Qiang Li
Although widely used in various fields due to its powerful capability of signal processing, empirical mode decomposition has to decompose signals separately, which limits its application for multivariate data such as the structural monitoring data record...
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Jozsef Pap, Csaba Mako, Miklos Illessy, Norbert Kis and Amir Mosavi
Identifying the performance factors of organizations is of utmost importance for labor studies for both empirical and theoretical research. The present study investigates the essential intra- and extra-organizational factors in determining the performanc...
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Wilson Tsakane Mongwe, Rendani Mbuvha and Tshilidzi Marwala
Markov chain Monte Carlo (MCMC) techniques are usually used to infer model parameters when closed-form inference is not feasible, with one of the simplest MCMC methods being the random walk Metropolis?Hastings (MH) algorithm. The MH algorithm suffers fro...
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Marta Galvani, Chiara Bardelli, Silvia Figini and Pietro Muliere
Bootstrap resampling techniques, introduced by Efron and Rubin, can be presented in a general Bayesian framework, approximating the statistical distribution of a statistical functional ϕ(F)" role="presentation">??(??)?(F)
?
(
F
)
, where F is a...
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Brina Miftahurrohmah,Catur Wulandari,Yogantara Setya Dharmawan
Pág. 11 - 21
Background: Stock investment has been gaining momentum in the past years due to the development of technology. During the pandemic lockdown, people have invested more. One the one hand, stock investment has high potential profitability, but on the other,...
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