In this paper, we explore the use of M-quantile regression and M-quantile coefficients to detect statistical differences between temporal curves that belong to different experimental conditions. In particular, we consider the application of temporal gene expression data. Here, the aim is to detect genes whose temporal expression is significantly different across a number of biological condition...

We introduce the local composite quantile regression (LCQR) to causal inference in discontinuity (RD) designs. Kai, Li and Zou study efficiency property of LCQR, while we show that its nice boundary performance translates accurate estimation treatment effects RD under a variety data generating processes. Moreover, propose bias-corrected standard error-adjusted t-test for inference, which leads ...

An algorithm for time-adaptive quantile regression is presented. The algorithm is based on the simplex algorithm, and the linear optimization formulation of the quantile regression problem is given. The observations have been split to allow a direct use of the simplex algorithm. The simplex method and an updating procedure are combined into a new algorithm for time-adaptive quantile regression,...

• The estimation of the extreme-value index γ based on a sample of independent and identically distributed random variables has received considerable attention in the extreme-value literature. However, the problem of combining data from several groups is hardly studied. In this paper we discuss the simultaneous estimation of tail indices when data on several independent data groups are availabl...

Numerous studies found mixed evidence on the effects of firm-related factors toward conditional distribution TFP performance done in a cross-country, industry, and firm-level perspectives abroad. Unfortunately, there is still relatively little to support these findings context Philippines. Thus, this study analyzed whether varies according size firms, forms ownership, examined impact such as fi...

Climate change may lead to changes in several aspects of the distribution of climate variables, including changes in the mean, increased variability, and severity of extreme events. In this paper, we propose using spatiotemporal quantile regression as a flexible and interpretable method for simultaneously detecting changes in several features of the distribution of climate variables. The spatio...