Results 21 to 30 of about 296,242 (293)
Frontiers in Public Health, 2021 This paper explores the necessity of expanding government expenditures on health (GEH) from the perspective of promoting residents' consumption (RC).
Ting-Yu Jiang
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A Robust Prediction Model for Species Distribution Using Bagging Ensembles with Deep Neural Networks
Remote Sensing, 2021 Species distribution models have been used for various purposes, such as conserving species, discovering potential habitats, and obtaining evolutionary insights by predicting species occurrence. Many statistical and machine-learning-based approaches have
Jehyeok Rew, Yongjang Cho, Eenjun Hwang
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SSRN Electronic Journal, 2011 We propose a methodology for constructing confidence regions with partially identified models of general form. The region is obtained by inverting a test of internal consistency of the econometric structure. We develop a dilation bootstrap methodology to deal with sampling uncertainty without reference to the hypothesized economic structure.
Galichon, Alfred, Henry, Marc
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Synthese, 2012 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Douven, Igor, Kelp, Christoph
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Sistem Informasi Penyewaan Kapal Berbasis Web (Studi Kasus : PT. Servewell Offshore)
Journal of Information Systems and Informatics, 2021 Transportasi laut sebagai bagian dari sistem transportasi nasional perlu dikembangkan dalam rangka mewujudkan Wawasan Nusantara yang mempersatukan seluruh wilayah Indonesia, termasuk lautan nusantara sebagai kesatuan wilayah nasional. Sistem transportasi
Nurullah Husufa +3 more
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SIAM Journal on Mathematics of Data Science, 2021 Probabilistic models of data sets often exhibit salient geometric structure. Such a phenomenon is summed up in the manifold distribution hypothesis, and can be exploited in probabilistic learning. Here we present normal-bundle bootstrap (NBB), a method that generates new data which preserve the geometric structure of a given data set.
Ruda Zhang, Roger Ghanem
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Using the Wild Bootstrap to Quantify Uncertainty in Mean Apparent Propagator MRI
Frontiers in Neuroinformatics, 2019 Purpose: Estimation of uncertainty of MAP-MRI metrics is an important topic, for several reasons. Bootstrap derived uncertainty, such as the standard deviation, provides valuable information, and can be incorporated in MAP-MRI studies to provide more ...
Xuan Gu +8 more
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Bootstrapping language acquisition [PDF]
Cognition, 2017 The semantic bootstrapping hypothesis proposes that children acquire their native language through exposure to sentences of the language paired with structured representations of their meaning, whose component substructures can be associated with words and syntactic structures used to express these concepts. The child's task is then to learn a language-
Abend, Omri +4 more
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Time Series Regression Modelling: Replication, Estimation and Aggregation through Maximum Entropy
Engineering Proceedings, 2023 In today’s world of large volumes of data, where the usual statistical estimation methods are commonly inefficient or, more often, impossible to use, aggregation methodologies have emerged as a solution for statistical inference.
Jorge Duarte, Maria Costa, Pedro Macedo
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Mathematics, 2021 Companies always seek ways to make their professional employees stay with them to reduce extra recruiting and training costs. Predicting whether a particular employee may leave or not will help the company to make preventive decisions.
Saeed Najafi-Zangeneh +3 more
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