Results 21 to 30 of about 170 (111)
On Asymptotic Mean Integrated Squared Error’s Reduction Techniques in Kernel Density Estimation
International Journal of Computational and Theoretical Statistics, 2019 The techniques of asymptotic mean integrated squared error’s reduction in kernel density estimation is the focus of this paper. The asymptotic mean integrated squared error (AMISE) is an optimality criterion function that measures the performance of a ...
I. U. Siloko +4 more
semanticscholar +1 more source
Semiparametric regression for circular response with application in ecology
Scandinavian Journal of Statistics, Volume 53, Issue 1, Page 54-101, March 2026.ABSTRACT A regression model for a circular response variable depending on a linear or a circular predictor is presented in this paper. The conditional density belongs to a parametric flexible family that allows for asymmetry and varying peakedness around the modal direction.
Jose Ameijeiras‐Alonso, Irène Gijbels
wiley +1 more source
An Adaptive SPH Method (ADP‐SPH) for Simulating Solute Transport in Heterogeneous Aquifers
Water Resources Research, Volume 61, Issue 12, December 2025.Abstract Smoothed Particle Hydrodynamics (SPH) is a meshfree, Lagrangian‐based approach used to solve the advection‐dispersion equation (ADE) of groundwater solute transport. It is well known that the accuracy of SPH deteriorates significantly when particles become irregularly distributed, often occurring in heterogeneous aquifers.
Tian Jiao +4 more
wiley +1 more source
A Novel Flexible Kernel Density Estimator for Multimodal Probability Density Functions
CAAI Transactions on Intelligence Technology, Volume 10, Issue 6, Page 1759-1782, December 2025.ABSTRACT Estimating probability density functions (PDFs) is critical in data analysis, particularly for complex multimodal distributions. traditional kernel density estimator (KDE) methods often face challenges in accurately capturing multimodal structures due to their uniform weighting scheme, leading to mode loss and degraded estimation accuracy ...
Jia‐Qi Chen +5 more
wiley +1 more source
Bandwidth selection for kernel intensity estimators for spatial point processes
Scandinavian Journal of Statistics, Volume 52, Issue 3, Page 1111-1137, September 2025.Abstract Intensity estimation through kernel smoothing is a popular non‐parametric method of describing the characteristics of an underlying spatial point process. Key to the accuracy of this estimate is the choice of bandwidth. Too large or small a bandwidth can lead to features in the intensity being lost or to the introduction of artefacts.
Bethany J. Macdonald +2 more
wiley +1 more source
Transactions in GIS, Volume 29, Issue 2, April 2025.ABSTRACT This paper addresses the use of nonparametric kernel density estimation (KDE) to estimate point‐based data density in spatial modeling using Geographic Information Systems (GIS). The paper highlights challenges in selecting the appropriate settings for generating the best fitting KDE surfaces and validating their accuracy, as many GIS packages
Michael Govorov +2 more
wiley +1 more source
Wind Energy, Volume 28, Issue 2, February 2025.ABSTRACT Wind speed variables play an important role in exploiting wind power. However, they are fluctuating and random. Therefore, understanding their characteristics and properties is necessary to improve exploitation efficiency. This research investigates various wind speed distribution models, both parametric and nonparametric, to estimate wind ...
Tin Trung Chau +3 more
wiley +1 more source
K-nearest neighbour kernel density estimation, the choice of optimal k
, 2011 The k-nearest neighbour kernel density estimationmethod is a special type of the kernel density estimation method with the local choice of the bandwidth. An advantage of this estimator is that smoothing varies according to the number of observations in a
Janne Orava
semanticscholar +1 more source
Friendlessness and loneliness: Cultural frames for making sense of disconnection
Canadian Review of Sociology/Revue canadienne de sociologie, Volume 62, Issue 1, Page 99-117, February 2025.Abstract This article is based on 21 interviews in an Atlantic Canadian city with people who identified as having few or no friends. With all the talk of a modern loneliness epidemic, we might easily assume friendless people are lonely, yet here we take an interpretive approach to analyze how they alternately claim to experience and not experience ...
Laura Eramian +2 more
wiley +1 more source
MODPATH‐RW: A Random Walk Particle Tracking Code for Solute Transport in Heterogeneous Aquifers
Groundwater, Volume 62, Issue 4, Page 617-634, July/August 2024.Abstract Random walk particle tracking (RWPT) is a discrete particle method that offers several advantages for simulating solute transport in heterogeneous geological systems. The formulation is a discrete solution to the advection‐dispersion equation, yielding results that are not influenced by grid‐related numerical dispersion.
Rodrigo Pérez‐Illanes +1 more
wiley +1 more source