Bayesian adaptive smoothing splines using stochastic differential equations

DOI10.1214/13-BA866zbMath1327.62234arXiv1209.2013MaRDI QIDQ899029

Yu Ryan Yue, Finn Lindgren, Håvard Rue, Daniel P. Simpson

Publication date: 21 December 2015

Published in: Bayesian Analysis (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1209.2013

zbMATH Keywords

stochastic differential equationMarkov chain Monte Carlosmoothing splineadaptive smoothing

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Nonparametric estimation (62G05) Bayesian inference (62F15) Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10)

Related Items

Posterior inference for sparse hierarchical non-stationary models, Multidimensional Adaptive P-Splines with Application to Neurons' Activity Studies, Bayesian modelling of time-varying conditional heteroscedasticity, Stable non-linear generalized Bayesian joint models for survival-longitudinal data, Hyperpriors for Matérn fields with applications in Bayesian inversion, Locally adaptive smoothing with Markov random fields and shrinkage priors, A unified view on Bayesian varying coefficient models, Flexible, boundary adapted, nonparametric methods for the estimation of univariate piecewise-smooth functions, Time-varying auto-regressive models for count time-series, Understanding the stochastic partial differential equation approach to smoothing

Uses Software

• gss
• GMRFLib
• SemiPar
• Fahrmeir
• gamair

Cites Work

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