Approximate inference for spatial functional data on massively parallel processors
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Publication:1623412
DOI10.1016/j.csda.2013.10.016zbMath1506.62152OpenAlexW2103097800WikidataQ60258621 ScholiaQ60258621MaRDI QIDQ1623412
Publication date: 23 November 2018
Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.csda.2013.10.016
Gaussian processesfunctional data analysisGPUlikelihood analysisfunctional mixed-effects modeloperator approximations
Computational methods for problems pertaining to statistics (62-08) Functional data analysis (62R10)
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Cites Work
- An Explicit Link between Gaussian Fields and Gaussian Markov Random Fields: The Stochastic Partial Differential Equation Approach
- Functional data analysis in an operator-based mixed-model framework
- Efficient two-dimensional smoothing with \(P\)-spline ANOVA mixed models and nested bases
- Inference for functional data with applications
- Priors for Bayesian adaptive spline smoothing
- Smoothing noisy data with spline functions: Estimating the correct degree of smoothing by the method of generalized cross-validation
- Longitudinal data with nonstationary errors: A nonparametric three-stage approach
- Growth curves: A two-stage nonparametric approach
- That BLUP is a good thing: The estimation of random effects. With comments and a rejoinder by the author
- Functional data analysis.
- Nonparametric functional data analysis. Theory and practice.
- Functional Mixed Effects Models
- A Penalized Spline Approach to Functional Mixed Effects Model Analysis
- Fast methods for spatially correlated multilevel functional data
- Maximum Likelihood Approaches to Variance Component Estimation and to Related Problems
- Mixed Effects Smoothing Spline Analysis of Variance
- Generalized Linear Models with Random Effects
- Spatially adaptive smoothing splines
- On the Relation Between Green's Functions and Covariances of Certain Stochastic Processes and Its Application to Unbiased Linear Prediction
- Variational optic flow computation with a spatio-temporal smoothness constraint
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