P-splines with derivative based penalties and tensor product smoothing of unevenly distributed data

DOI10.1007/s11222-016-9666-xzbMath1384.65020arXiv1605.02446OpenAlexW2383878747WikidataQ59614132 ScholiaQ59614132MaRDI QIDQ1703813

Simon N. Wood

Publication date: 7 March 2018

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1605.02446

zbMATH Keywords

smoothing splineP-splineBayesian stochastic simulationderivative penaltyreduced rank splinetensor product smooth

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Numerical computation using splines (65D07)

Related Items

Optimally adaptive Bayesian spectral density estimation for stationary and nonstationary processes, Bayesian spectral density estimation using P-splines with quantile-based knot placement, Inference and computation with generalized additive models and their extensions, Spline local basis methods for nonparametric density estimation, Longitudinal modeling of age-dependent latent traits with generalized additive latent and mixed models

Uses Software

• CSparse

Cites Work

• Penalized splines for smooth representation of high-dimensional Monte Carlo datasets
• A comparison of GCV and GML for choosing the smoothing parameter in the generalized spline smoothing problem
• A practical guide to splines
• Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
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• ON SEMIPARAMETRIC REGRESSION WITH O'SULLIVAN PENALIZED SPLINES
• Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models
• Parameter Estimation for Differential Equations: a Generalized Smoothing Approach
• Low‐Rank Scale‐Invariant Tensor Product Smooths for Generalized Additive Mixed Models
• A practical guide to splines.
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