Results 81 to 90 of about 3,477,506 (374)

Probabilistic Solar Forecasting Using Quantile Regression Models

Energies, 2017
In this work, we assess the performance of three probabilistic models for intra-day solar forecasting. More precisely, a linear quantile regression method is used to build three models for generating 1 h–6 h-ahead probabilistic forecasts. Our approach is
Philippe Lauret, Mathieu David, Hugo T. C. Pedro   +2 more
doaj   +1 more source

Shadow prices and marginal abatement costs: Convex quantile regression approach

European Journal of Operational Research, 2021
Marginal abatement cost (MAC) is a critically important concept for efficient environmental policy and management. In this paper we argue that most empirical studies using frontier estimation methods such as data envelopment analysis (DEA) over-estimate ...
Timo Kuosmanen, Xun Zhou
semanticscholar   +1 more source

Bayesian analysis of a Tobit quantile regression model [PDF]

, 2007
This paper develops a Bayesian framework for Tobit quantile regression. Our approach is organized around a likelihood function that is based on the asymmetric Laplace dis- tribution, a choice that turns out to be natural in this context.
Stander, J, Yu, K
core   +1 more source

Mapping Genetic Regulation of Transcription to Identify Functional Variants and Genes Associated with Pancreatic Cancer Risk

Advanced Science, EarlyView.
Integration of a pancreatic eQTL map with a GWAS meta‐analysis identifies 82 putative functional variants and 15 genes. The association between rs11102484 and pancreatic cancer risk is observed in a total of 5699 cases and 8467 controls. The G allele of rs11102484 weakens ZNF263 binding and the silencer‐promoter interaction, thereby increasing ST7L ...
Xiaoyang Wang, Hui Geng, Zhengyan Yao, Yuan Jiang, Can Chen, Zequn Lu, Shuangshuang Tian, Ming Zhang, Ruiyan Liu, Chenxi Feng, Bin Li, Xiaoping Miao, Jianbo Tian, Shaokai Zhang, Ying Zhu   +14 more
wiley   +1 more source

Unit-Modified Weibull Distribution and Quantile Regression Model [PDF]

Anais da Academia Brasileira de Ciências
The 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, CLEBER BISOGNIN, RENATA ROJAS GUERRA, FÁBIO M. BAYER   +3 more
doaj   +1 more source

Organ‐Specific and Conserved Regulatory Logic Orchestrates Gene Expression in the Embryonic Mesothelium

Advanced Science, EarlyView.
Integrated multi‐omic profiling maps the gene‐regulatory landscape of the coelomic mesothelium across heart, lung, and pancreas. A cardiac‐restricted regulatory program is uncovered in which TBX20 activates heart mesothelial (epicardial) cis‐regulatory elements, while MAF emerges as a conserved regulator of mesothelial identity.
Quang Minh Dang, Nicola Smart, Andia Nicole Redpath, Joaquim Miguel Vieira   +3 more
wiley   +1 more source

Efficient quantile regression for heteroscedastic models [PDF]

, 2014
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.
Jung, Yoonsuh, Lee, Yoonkyung, MacEachern, Steve N,   +2 more
core   +3 more sources

Cognitive Trajectories from Preclinical Alzheimer's Disease to Dementia

Advanced Science, EarlyView.
A continuous, multi‐domain characterization of cognitive decline across the Alzheimer's disease spectrum identifies when individual cognitive measures become abnormal. Episodic memory declines first, followed by executive function, language, processing speed, and visuospatial abilities, supporting improved clinical interpretation and optimized endpoint
Fredrik Öhman, Lars Lau Raket, Michael Schöll, for the Alzheimer's Disease Neuroimaging Initiative†   +3 more
wiley   +1 more source

bayesQR: A Bayesian Approach to Quantile Regression

Journal of Statistical Software, 2017
After its introduction by Koenker and Basset (1978), quantile regression has become an important and popular tool to investigate the conditional response distribution in regression. The R package bayesQR contains a number of routines to estimate quantile
Dries F. Benoit, Dirk Van den Poel
doaj   +1 more source

Comparing Five Machine Learning-Based Regression Models for Predicting the Study Period of Mathematics Students at IPB University

JTAM (Jurnal Teori dan Aplikasi Matematika), 2022
Grade point average (GPA) is initial information for supervisors to characterize their supervised students. One model that can be used to predict a student's study period based on GPA is a machine learning-based regression model so that supervisors can ...
Sri Nurdiati, Mohamad Khoirun Najib
doaj   +1 more source