Bayesian inference in based-kernel regression: comparison of count data of condition factor of fish in pond systems

DOI10.1080/02664763.2020.1830953OpenAlexW3092176218MaRDI QIDQ5085642

Tristan Senga Kiessé, Joël Aubin, Étienne Rivot, Christophe Jaeger

Publication date: 27 June 2022

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2020.1830953

zbMATH Keywords

uncertainty analysisaquacultureprior and posterior distributionsdiscrete kernelfishpond

Mathematics Subject Classification ID

Density estimation (62G07) Nonparametric estimation (62G05) Point estimation (62F10) Bayesian inference (62F15) Applications of statistics (62Pxx)

Uses Software

• rjags
• JAGS
• BayesDA

Cites Work

• Unnamed Item
• Beta kernel estimators for density functions
• Local multiplicative bias correction for asymmetric kernel density estimators
• On semiparametric regression for count explanatory variables
• Discrete associated kernels method and extensions
• Bayesian estimation of bandwidth in semiparametric kernel estimation of unknown probability mass and regression functions of count data
• A comparison of cross-validation techniques in density estimation
• Multiplicative bias correction for discrete kernels
• Comparison study to bandwidth selection in binomial kernel estimation using Bayesian approaches
• Introduction to Hierarchical Bayesian Modeling for Ecological Data
• On finite sample properties of nonparametric discrete asymmetric kernel estimators
• Bayesian nonparametric hierarchical modeling
• Discrete triangular distributions and non-parametric estimation for probability mass function
• Probability
• Introduction to nonparametric estimation

This page was built for publication: Bayesian inference in based-kernel regression: comparison of count data of condition factor of fish in pond systems