Results 1 to 10 of about 3,403,709 (354)
Bandwidth selection for the Wolverton–Wagner estimator [PDF]
Journal of Statistical Planning and Inference, 2020 26 pages, 5 ...
Fabienne Comte, Nicolas Marie
semanticscholar +6 more sources
Bandwidth selection in pre-smoothed particle filters [PDF]
Statistics and Computing, 2012 For the purpose of maximum likelihood estimation of static parameters, we apply a kernel smoother to the particles in the standard SIR filter for non-linear state space models with additive Gaussian observation noise. This reduces the Monte Carlo error in the estimates of both the posterior density of the states and the marginal density of the ...
Kleppe, Tore Selland, Skaug, Hans J.
openaire +4 more sources
Optimal Bandwidth Selection Methods with Application to Wind Speed Distribution [PDF]
Mathematics, 2023 Accurate estimation of the unknown probability density functions of critical variables, such as wind speed—which plays a pivotal role in harnessing clean energy—is essential for various scientific and practical applications.
Necla Gündüz, Şule Karakoç
doaj +2 more sources
Automatic bandwidth selection for circular density estimation [PDF]
Computational Statistics & Data Analysis, 2008 Given angular data θ1,…,θn[0,2π) a common objective is to estimate the density. In case that a kernel estimator is used, bandwidth selection is crucial to the performance.
Taylor, C.C.
core +4 more sources
Bootstrap Bandwidth Selection Using anh‐Dependent Pilot Bandwidth [PDF]
Scandinavian Journal of Statistics, 2008 Abstract. The problem of choosing the bandwidthhfor kernel density estimation is considered. All the plug‐in‐type bandwidth selection methods require the use of a pilot bandwidthg. The usual way to make anh‐dependent choice ofgis by obtaining their asymptotic expressions separately and solving the two equations.
Chacón, José E. +2 more
openaire +3 more sources
Bandwidth Selection for Prediction in Regression [PDF]
Proceedings, 2019 There exist many different methods to choose the bandwidth in kernel regression. If, however, the target is regression based prediction for samples or populations with potentially different distributions, then the existing methods can easily be ...
Inés Barbeito +2 more
doaj +3 more sources
New Bandwidth Selection for Kernel Quantile Estimators [PDF]
Journal of Probability and Statistics, 2012 We propose a cross-validation method suitable for smoothing of kernel quantile estimators. In particular, our proposed method selects the bandwidth parameter, which is known to play a crucial role in kernel smoothing, based on unbiased estimation of a ...
Ali Al-Kenani, Keming Yu
doaj +5 more sources
Optimal bandwidth selection in stochastic regression of Bio-FET measurements. [PDF]
J Math BiolMelara LA +4 more
europepmc +3 more sources
Conditional Kaplan–Meier Estimator with Functional Covariates for Time-to-Event Data
Stats, 2022 Due to the wide availability of functional data from multiple disciplines, the studies of functional data analysis have become popular in the recent literature. However, the related development in censored survival data has been relatively sparse.
Sudaraka Tholkage +2 more
doaj +1 more source
Energies, 2022 This paper proposes a wind power probabilistic model (WPPM) using the reflection method and multi-kernel function kernel density estimation (KDE).
Juseung Choi +2 more
doaj +1 more source