This work reviews the literature on spline local basis methods for non-parametric density
estimation. Particular attention is paid to B-spline density estimators which have …

Spatial quantile autoregression for season within year daily maximum temperature data
Page 1 The Annals of Applied Statistics 2023, Vol. 17, No. 3, 2305–2325 https://doi.org/10.1214/22-AOAS1719 …

We present a novel class of projected methods to perform statistical analysis on a data set of
probability distributions on the real line, with the 2-Wasserstein metric. We focus in particular …

Bayesian methods for non-parametric quantile regression have been considered with
multiple continuous predictors ranging values in the unit interval. Two methods are …

Applying quantile regression to count data presents logical and practical complications
which are usually solved by artificially smoothing the discrete response variable through …

Quantile regression (QR) has gained popularity during the last decades, and is now
considered a standard method by applied statisticians and practitioners in various fields. In …

Recent outbreak of the novel corona virus COVID-19 has affected all of our lives in one way
or the other. While medical researchers are working hard to find a cure and doctors/nurses …

Quantile regression continues to increase in usage, providing a useful alternative to
customary mean regression. Primary implementation takes the form of so-called multiple …

The extension of quantile regression to count data raises several issues. We compare the
traditional approach, based on transforming the count variable using jittering, with a recently …

Purpose With the rise of mandating climate-related disclosures (CRD), this paper aims to
investigate how energy and agriculture markets are exposed to climate disclosure risk …