Results 71 to 80 of about 2,542,650 (299)
Spatial quantile regression in analysis of mortality
Acta Universitatis Lodziensis. Folia Oeconomica, 2016 The paper concerns mortality in Poland. The aim of the article is to identify factors determining average life length of men and women in 66 subregions of Poland.
Grażyna Trzpiot +1 more
doaj +1 more source
Functional coefficient quantile regression model with time-varying loadings
Journal of Applied Economics, 2023 This paper proposes a functional coefficient quantile regression model with heterogeneous and time-varying regression coefficients and factor loadings. Estimation of the model coefficients is done in two stages.
Alev Atak +2 more
doaj +1 more source
Predictions in Quantile Regressions
Open Journal of Statistics, 2014 Two different tools to evaluate quantile regression forecasts are proposed: MAD, to summarize forecast errors, and a fluctuation test to evaluate in-sample predictions. The scores of the PISA test to evaluate students’ proficiency are considered. Growth analysis relates school attainment to economic growth.
openaire +3 more sources
Vector quantile regression [PDF]
We propose a notion of conditional vector quantile function and a vector quantile regression. A conditional vector quantile function (CVQF) of a random vector Y, taking values in ℝd given covariates Z=z, taking values in ℝk, is a map u↦QY∣Z(u,z), which is monotone, in the sense of being a gradient of a convex function, and such that given that vector U
Guillaume Carlier +2 more
openaire +4 more sources
Artificial Intelligence‐Guided Phenotypic Drug Repurposing Against Streptococcus pneumoniae
Advanced Science, EarlyView.Integrated artificial intelligence (AI) ensembles identify highly potent repurposed drugs against Streptococcus pneumoniae. Prospective virtual screening of 6747 drugs uncovers nine active candidates, including thiostrepton. This drug exhibits low picomolar potency and bypasses established resistance in multidrug‐resistant strains, demonstrating an ...
Joshua S. Fitch +6 more
wiley +1 more source
An Improved Interior Point Algorithm for Quantile Regression
IEEE Access, 2020 Quantile regression is a powerful statistical technique for estimating the quantiles of a conditional distribution on the values of covariates. It has been widely used in many fields.
Pan Zhao, Shenghua Yu
doaj +1 more source
Conformalized Quantile Regression
, 2019 Conformal prediction is a technique for constructing prediction intervals that attain valid coverage in finite samples, without making distributional assumptions. Despite this appeal, existing conformal methods can be unnecessarily conservative because they form intervals of constant or weakly varying length across the input space.
Yaniv Romano +2 more
openaire +3 more sources
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 +12 more
wiley +1 more source
Censored Quantile Regression Forest
CoRR, 2019 Random forests are powerful non-parametric regression method but are severely limited in their usage in the presence of randomly censored observations, and naively applied can exhibit poor predictive performance due to the incurred biases. Based on a local adaptive representation of random forests, we develop its regression adjustment for randomly ...
Li, Alexander Hanbo, Bradic, Jelena
openaire +7 more sources
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 +7 more
wiley +1 more source