Results 151 to 160 of about 30,733 (250)
Partial Linear Quantile Regression and Bootstrap Confidence Bands [PDF]
In this paper uniform confidence bands are constructed for nonparametric quantile estimates of regression functions. The method is based on the bootstrap, where resampling is done from a suitably estimated empirical density function (edf) for residuals ...
Song Song +2 more
core
Vadose Zone Journal, Volume 25, Issue 3, May/June 2026.Abstract Previously, developers of soil moisture monitoring networks have determined how many sensors to use and their installation depths with little objective guidance, which led to heavy reliance on suboptimal past precedents when deploying new networks. One such network, the Oklahoma Hydronet, is being developed to monitor water stored in the state'
Erik S. Krueger +7 more
wiley +1 more source
The Stochastic Fluctuation of the Quantile Regression Curve [PDF]
Let (X1, Y1), . . ., (Xn, Yn) be i.i.d. rvs and let l(x) be the unknown p-quantile regression curve of Y on X. A quantile-smoother ln(x) is a localised, nonlinear estimator of l(x).
Song Song, Wolfgang Härdle
core
Earth's Future, Volume 14, Issue 5, May 2026.Abstract Bayesian Causal Networks (BCNs) are adapted to investigate causal factors of hydroclimate variability in the Brahmaputra River Basin (BRB) during the seasonal and sub‐seasonal periods. This is the longest monsoonal river system in India, prone to frequent severe flooding.
Naman Kishan Rastogi +2 more
wiley +1 more source
EkonometriaThis work addresses the problem of the nonparametric estimation of the regression function, namely the conditional distribution and the conditional quantile in the single functional index model (SFIM) under the independent and identically distributed ...
Anis Allal, Nadia Kadiri, Abbes Rabhi
doaj
How do ecologists estimate occupancy in practice?
Ecography, Volume 2026, Issue 5, May 2026.Over 20 years ago, ecologists were introduced to the site occupancy model (SOM) for estimating occupancy rates from detection‐nondetection data. In the ensuing decades, the SOM and its hierarchical modeling extensions have become mainstays of quantitative ecology, and estimating occupancy rates has become one of the most common applications of ...
Benjamin R. Goldstein +9 more
wiley +1 more source
Monitoring panels of sparse functional data
Journal of Time Series Analysis, Volume 47, Issue 3, Page 660-674, May 2026.Panels of random functions are common in applications of functional data analysis. They often occur when sequences of functions are observed at a number of different locations. We propose a methodology to monitor for structural breaks in such panels and to identify the changing components with statistical certainty.
Tim Kutta +2 more
wiley +1 more source
Gradual Changes in Functional Time Series
Journal of Time Series Analysis, Volume 47, Issue 3, Page 632-650, May 2026.ABSTRACT We consider the problem of detecting gradual changes in the sequence of mean functions from a not necessarily stationary functional time series. Our approach is based on the maximum deviation (calculated over a given time interval) between a benchmark function and the mean functions at different time points.
Patrick Bastian, Holger Dette
wiley +1 more source
Modeling insurance claims using Bayesian nonparametric regression. [PDF]
PLoS OneShams M, Ghosh K.
europepmc +1 more source
Journal of Time Series Analysis, Volume 47, Issue 3, Page 539-556, May 2026.ABSTRACT In this paper, we propose a new test for the detection of a change in a non‐linear (auto‐)regressive time series as well as a corresponding estimator for the unknown time point of the change. To this end, we consider an at‐most‐one‐change model and approximate the unknown (auto‐)regression function by a neural network with one hidden layer. It
Claudia Kirch, Stefanie Schwaar
wiley +1 more source