An SVM-like approach for expectile regression
نویسندگان
چکیده
منابع مشابه
On confidence intervals for semiparametric expectile regression
In regression scenarios there is a growing demand for information on the conditional distribution of the response beyond the mean. In this scenario quantile regression is an established method of tail analysis. It is well understood in terms of asymptotic properties and estimation quality. Another way to look at the tail of a distribution is via expectiles. They provide a valuable alternative s...
متن کاملLearning Rates for Kernel-Based Expectile Regression
Conditional expectiles are becoming an increasingly important tool in finance as well as in other areas of applications. We analyse a support vector machine type approach for estimating conditional expectiles and establish learning rates that are minimax optimal modulo a logarithmic factor if Gaussian RBF kernels are used and the desired expectile is smooth in a Besov sense. As a special case, ...
متن کاملNonparametric Multiple Expectile Regression via ER-Boost
Expectile regression (Newey & Powell 1987) is a nice tool for estimating the conditional expectiles of a response variable given a set of covariates. Expectile regression at 50% level is the classical conditional mean regression. In many real applications having multiple expectiles at different levels provides a more complete picture of the conditional distribution of the response variable. Mul...
متن کاملBayesian regularisation in geoadditive expectile regression
Abstract Regression classes modeling more than the mean of the response have found a lot of attention in the last years. Expectile regression is a special and computationally convenient case of this family of models. Expectiles offer a quantile-like characterisation of a complete distribution and include the mean as a special case. In the frequentist framework the impact of a lot of covariates ...
متن کاملAn imprecise boosting-like approach to regression
This paper is about a generalization of ensemble methods for regression which are based on variants of the basic AdaBoost algorithm. The generalization of these regression methods consists in restricting the unit simplex for the weights of the instances to a smaller set of weighting probabilities. The proposed algorithms cover the standard AdaBoost-based regression algorithms and standard regre...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Computational Statistics & Data Analysis
سال: 2017
ISSN: 0167-9473
DOI: 10.1016/j.csda.2016.11.010