Results 81 to 90 of about 2,329,699 (248)

Performance Quantile Regression and Bayesian Quantile Regression in Dealing with Non-normal Errors (Case Study on Simulated Data)

Numerical: Jurnal Matematika dan Pendidikan Matematika
This 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, Ferra Yanuar, Vika Pradinda Harahap, Latifatul Qalbi   +3 more
doaj   +1 more source

Online Quantile Regression

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
openaire   +3 more sources

Partially linear censored quantile regression [PDF]

, 2009
Censored regression quantile (CRQ) methods provide a powerful and flexible approach to the analysis of censored survival data when standard linear models are felt to be appropriate.
Portnoy, S., Neocleous, T.
core   +1 more source

Conditionally Significant eQTL and TWAS Analyses Identify MsRD26 as a Major Candidate Positive Regulator of Salt Tolerance in Medicago sativa L

Advanced Science, EarlyView.
Salt stress significantly impacts plant growth. Through population transcriptome, eQTL and TWAS analyses, we identified several candidate genes potentially associated with salt stress response. Functional assays suggested that some of these genes may contribute to salt tolerance.
Lin Chen, Yuqi Zhang, Xinyue Ma, Jinpeng Bi, Fei He, Li Zhao, Haiyue Lei, Zhengqin Xiao, Xue Wang, Tiejun Zhang, Ruicai Long, Junmei Kang, Qingchuan Yang   +12 more
wiley   +1 more source

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
core  

Efficient quantile regression for heteroscedastic models [PDF]

, 2015
Quantile regression (QR) provides estimates of a range of conditional quantiles. This stands in contrast to traditional regression techniques, which focus on a single conditional mean function. Lee et al.
MacEachern, Steve N,, Lee, Yoonkyung, Jung, Yoonsuh, Steven N. Maceachern, MacEachern, Steven N., Yoonsuh Jung, Yoonkyung Lee, Yoonsuh Jung (111157), Yoonkyung Lee (643212), Steven N. MacEachern (638105)   +9 more
core   +1 more source

Highly Sensitive Spatial Host‐Microbiome Transcriptomics in FFPE Tissues via Iterative Hydrogel Expansion

Advanced Science, EarlyView.
Ex‐spRandom is a spatial transcriptomics platform that synergizes random‐primed chemistry with iterative hydrogel expansion. By physically decrowding the dense FFPE matrix, this scalable technology shatters the traditional resolution‐sensitivity barrier.
Shunji Zhang, Mengyuan Wang, Jiaye Chen, Yuyi Zhu, Bin Zhu, Ziye Xu, Yuan Liao, Yongcheng Wang   +7 more
wiley   +1 more source

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, Maurício Vaz Lobo Bittencourt   +1 more
doaj   +1 more source

Low Latency Global Carbon Budget Reveals Late 2024 Carbon Losses and Contrasting Early 2025 Land Sink Recovery Signals

Advanced Science, EarlyView.
Low latency carbon budget estimates for July 2024–June 2025 combine atmospheric CO2 growth rates, fossil emissions, ocean uptake, DGVM land fluxes, and OCO‐2 inversions. The budget shows that late‐2024 land carbon losses dominate the annual anomaly, while early‐2025 recovery differs between bottom‐up models and top‐down inversions, especially in ...
Piyu Ke, Philippe Ciais, Yitong Yao, Stephen Sitch, Wei Li, Xiaomeng Du, Xiaofan Gui, Ben Poulter, Thomas Colligan, Auke M. van der Woude, Joram Hooghiem, Wouter Peters, Zhu Liu, Zhu Deng, Zhe Jin, Xiangjun Tian, Yilong Wang, Junjie Liu, Sudhanshu Pandey, Chris O'Dell, Jiang Bian, John Miller, Xin Lan, Jefferson Goncalves De Souza, Michael O'Sullivan, Pierre Friedlingstein, Julien Alléon, Yi Xi, Daniel S. Goll, Lei Zhu, Guido R. van der Werf, Shilong Piao, Frédéric Chevallier   +32 more
wiley   +1 more source

Similarity‐Enhanced Representation Learning of Non‐Canonical Amino Acids for Therapeutic Peptide Modeling

Advanced Science, EarlyView.
Non‐canonical amino acids (ncAAs) enhance peptide therapeutics but remain difficult to model computationally. SinCAA, a similarity‐enhanced pretraining framework, jointly optimizes contrastive learning guided by a novel conformational similarity metric with masked node reconstruction, capturing both functional relationships and chemical identity of ...
Chencheng Xu, Lesong Wei, Jianmin Wang, Yuanpeng Xiong, Ruochi Zhang, Yu Wang, Chao Zha, Qiangcheng Zeng, Xin Gao   +8 more
wiley   +1 more source