It is generally accepted that climate change is having a negative impact on food security.
However, most of the literature variously focuses on the complex and many mechanisms …

The study investigates whether changes in bank competition, efficiency, and risk-taking
affect the profitability of Indian commercial banks during 1996− 2016. While assessing the …

Varying coefficient models are a flexible extension of generic parametric models whose
coefficients are functions of a set of effect-modifying covariates instead of fitted constants …

A general class of non-stationary time series is considered in this paper. We estimate the
time-varying coefficients by using local linear M-estimation. For these estimators, weak …

Abstract Model average techniques are very useful for model-based prediction. However,
most earlier works in this field focused on parametric models and continuous responses. In …

Varying coefficient models (VCMs) are widely used for estimating nonlinear regression
functions for functional data. Their Bayesian variants using Gaussian process priors on the …

In this article, we propose a novel nonparametric statistical learning tool based on modal
regression, which can complement the standard mean and quantile regression and has …

The multiscale geographically weighted regression (MGWR) model is a useful extension of
the geographically weighted regression (GWR) model. MGWR, however, is a kind of …

Let Y be an outcome of interest, X a vector of treatment measures, and W a vector of pre-
treatment control variables. Here X may include (combinations of) continuous, discrete, or …

The reconstruction of gene regulatory networks (GRNs) from data is vital in systems biology.
Although different approaches have been proposed to infer causality from data, some …