Results 91 to 100 of about 2,542,650 (299)
Unit-Modified Weibull Distribution and Quantile Regression Model [PDF]
Anais da Academia Brasileira de CiênciasThe Sustainable Development Goals (SDGs) of the United Nations consist of 17 general objectives, subdivided into 169 targets to be achieved by 2030. Several SDG indices and indicators require continuous analysis and evaluation, and most of these indices ...
JOÃO INÁCIO SCRIMINI +3 more
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Numerical: Jurnal Matematika dan Pendidikan MatematikaThis research discusses the performance of quantile regression and Bayesian quantile regression methods. Quantile regression uses parameter estimation by maximizing the value of the likelihood function, while Bayesian quantile regression uses parameter ...
Lilis Harianti Hasibuan +3 more
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J. Mach. Learn. Res.The revised version substantially improves both the theory and the numeric experiments. In Theorem1 of the current manuscript, it only requires geometrically decaying step size, with great parameter flexibility. In the current manuscript, this noise moment assumption is significantly weakened to only require $\EE|\xi|<+\infty$
Yinan Shen, Dong Xia, Wen-Xin Zhou
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Advanced Science, EarlyView.Pathological tissue rigidity mechanoprimes microglia by enhancing actin cytoskeleton–nucleus coupling and chromatin opening at rigidity‐responsive cis‐regulatory elements (mechanoCREs). Subsequent NF‐κB/p65 signaling converges on this permissive regulatory state to amplify inflammatory gene expression and microglial activation.
Yu Xuan Meng +15 more
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Quantile Regression Learning with Coefficient Dependent lq-Regularizer
MATEC Web of Conferences, 2018 In this paper, We focus on conditional quantile regression learning algorithms based on the pinball loss and lq-regularizer with 1≤q≤2. Our main goal is to study the consistency of this kind of regularized quantile regression learning. With concentration
Sun Pengju, Li Meng, Sun Hongwei
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Using Quantile Regression for Duration Analysis [PDF]
Quantile regression methods are emerging as a popular technique in econometrics and biometrics for exploring the distribution of duration data. This paper discusses quantile regression for duration analysis allowing for a flexible specification of the ...
Wilke, Ralf A., Fitzenberger, Bernd
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Advanced Science, EarlyView.By integrating 516 whole‐genome resequencing datasets and 236 transcriptomes of allotetraploid common carp, this study establishes the first population‐scale atlas of transposable element (TE) variation in teleost species. TE bursts, relaxed purifying selection, and lineage‐specific loss of ancient insertions shape genome evolution and phenotypic ...
Shuimu Hu +11 more
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Quantile Regression with Censoring and Endogeneity [PDF]
In this paper, we develop a new censored quantile instrumental variable (CQIV) estimator and describe its properties and computation. The CQIV estimator combines Powell (1986) censored quantile regression (CQR) to deal semiparametrically with censoring ...
Amanda Kowalski +2 more
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Structured additive quantile regression with applications to modelling undernutrition and obesity of children [PDF]
, 2012 Quantile regression allows to model the complete conditional distribution of a response variable - expressed by its quantiles - depending on covariates, and thereby extends classical regression models which mainly address the conditional mean of a ...
Fenske, Nora
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Public-private income gap in Brazil: a counterfactual analysis
Economia & Região, 2017 The study investigated the gap of public-private income through the Decomposition of OaxacaBlinder, quantile regression and Melly’s Quantile Decomposition through the PNAD data of 2013.
Raphael Gomes Brasil +1 more
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