Smooth additive mixed models for predicting aboveground biomass
From MaRDI portal
Publication:2403468
DOI10.1007/s13253-016-0271-4zbMath1373.62563OpenAlexW2560741154WikidataQ58928151 ScholiaQ58928151MaRDI QIDQ2403468
Hortensia Sixto, Mariola Sánchez-González, Isabel Cañellas, Dae-Jin Lee, María Durbán
Publication date: 8 September 2017
Published in: Journal of Agricultural, Biological, and Environmental Statistics (Search for Journal in Brave)
Full work available at URL: http://hdl.handle.net/20.500.11824/326
Applications of statistics to environmental and related topics (62P12) Generalized linear models (logistic models) (62J12)
Related Items (2)
Tensor cubic smoothing splines in designed experiments requiring residual modelling ⋮ A general framework for prediction in penalized regression
Uses Software
Cites Work
- Unnamed Item
- Efficient two-dimensional smoothing with \(P\)-spline ANOVA mixed models and nested bases
- Straightforward intermediate rank tensor product smoothing in mixed models
- Fast and compact smoothing on large multidimensional grids
- Wavelet regression estimation in nonparametric mixed effect models
- Flexible smoothing with \(B\)-splines and penalties. With comments and a rejoinder by the authors
- Generalized Linear Array Models with Applications to Multidimensional Smoothing
- Flexible smoothing with P-splines: a unified approach
- Semiparametric Regression
- P-spline ANOVA-type interaction models for spatio-temporal smoothing
- Low‐Rank Scale‐Invariant Tensor Product Smooths for Generalized Additive Mixed Models
- Recovery of inter-block information when block sizes are unequal
This page was built for publication: Smooth additive mixed models for predicting aboveground biomass
