http://school.freekaoyan.com/sx/xjtu/daoshi/2024/06-27/16247910031519951.shtml WebMar 18, 2024 · R Documentation Expectiles of distributions Description Much like the 0.5 quantile of a distribution is the median, the 0.5 expectile is the mean / expected value. These functions add the possibility of calculating expectiles of known distributions.
Expectile and Quantile Regression and Other Extensions
WebJun 17, 2024 · The iterative local adaptive majorize-minimize (ILAMM) algorithm is employed for computing L1 -penalized and iteratively reweighted L1 -penalized (IRW- L1) (robust) expectile regression estimates. Special cases include penalized least … WebNov 28, 2024 · The Barzilai-Borwein gradient descent algorithm, initialized at a Huberized expectile regression estimate, is used to compute conquer estimators. This algorithm is scalable to very large-scale datasets. For R implementation, see the conquer package on CRAN (also embedded in quantreg as an alternative approach to fn and pfn). folding cart on wheels costco
Expectile regression forest: A new nonparametric expectile regression ...
WebAsymmetric least squares (expectile regression), e.g., for normal, Poisson, binomial, exponential, Asymmetric Laplace distribution, Gumbel, GEV, GPD models- for extreme value data. Reduced-rank VGLMs e.g., RR-negative binomial (akaNB-P), e.g., RR-multinomial (akastereotype model), RR-Gaussian, etc. , Webthe ˇth conditional expectile of Y neither from itself nor from its association with P S ˇ X. We call P S ˇ X the material part of X and Q S ˇ X the immaterial partofX. Remark 1. … WebJul 8, 2024 · An expectile is the minimizer of an asymmetric least squares criterion, making it a weighted average. This also means that an expectile is the conditional mean of the distribution under special circumstances. Specifically, an expectile of a distribution is a value that would be the mean if values above it were more likely to occur than they are. egmt telearchives