Bandwidth selection for kernel log-density estimation
type: Item
instance of: scholarly article
title: Bandwidth selection for kernel log-density estimation
zbMATH Open document ID: 1466.62092
author: Martin L. Hazelton
author: Murray P. Cox
published in: Computational Statistics and Data Analysis
publication date: 2018-08-15T00:00:00Z
Mathematics Subject Classification ID: 62-08
Mathematics Subject Classification ID: 62G07
zbMATH DE Number: 6918214
zbMATH Keywords: approximate likelihood inference
zbMATH Keywords: kernel smoothing
zbMATH Keywords: mean squared error
zbMATH Keywords: simulation
zbMATH Keywords: smooth cross-validation
describes a project that uses: KernSmooth
describes a project that uses: pyuvdata
MaRDI profile type: Publication
full work available at URL: j.csda.2016.05.003
OpenAlex ID: W2354270012
cites work: Adaptive approximate Bayesian computation
cites work: Q5186563
cites work: Plug-in bandwidth matrices for bivariate kernel density estimation
cites work: Cross-validation Bandwidth Matrices for Multivariate Kernel Density Estimation
cites work: Smoothed cross-validation
cites work: On the estimation of entropy
cites work: Q4893045
cites work: Inference Based on Kernel Estimates of the Relative Risk Function in Geographical Epidemiology
cites work: Kernel estimation of relative risk
cites work: Local likelihood density estimation
cites work: Approximate Bayesian computational methods
cites work: Fast Computation of Fully Automated Log-Density and Log-Hazard Estimators
cites work: Q3330303
cites work: Q4272483
cites work: On the estimation of a probability density function by the maximum penalized likelihood method
cites work: Comparison of Smoothing Parameterizations in Bivariate Kernel Density Estimation
cites work: Multivariate plug-in bandwidth selection
DOI: 10.1016/J.CSDA.2016.05.003
description: scientific article; zbMATH DE number 6918214