Robust Ranking of Happiness Outcomes: A Median Regression Perspective

Robust Regression by Boosting the Median

Most boosting regression algorithms use the weighted average of base regressors as their final regressor. In this paper we analyze the choice of the weighted median. We propose a general boosting algorithm based on this approach. We prove boosting-type convergence of the algorithm and give clear conditions for the convergence of the robust training error. The algorithm recovers ADABOOST and ADA...

Robust Nonparametric Estimation via Wavelet Median Regression

In this paper we develop a nonparametric regression method that is simultaneously adaptive over a wide range of function classes for the regression function and robust over a large collection of error distributions, including those that are heavy-tailed, and may not even possess variances or means. Our approach is to first use local medians to turn the problem of nonparametric regression with u...

Robust PLS regression based on simple least median squares regression

individual qualities and integrative motivation and their prediction of non-linguistic outcomes of learning english in intermediate iranian students: a psychological perspective

abstract this study investigated the predictability of variables from a motivational framework as well as individuals qualities to predict three non-linguistic outcomes of language learning. gardners socio-educational model with its measures has been used in the current study. individual qualities presented in this study include (1) age, (2) gender, and (3) language learning experience. the...

Bayesian latent variable models for median regression on multiple outcomes.

Often a response of interest cannot be measured directly and it is necessary to rely on multiple surrogates, which can be assumed to be conditionally independent given the latent response and observed covariates. Latent response models typically assume that residual densities are Gaussian. This article proposes a Bayesian median regression modeling approach, which avoids parametric assumptions ...