Data · dataset · 2015
Functional Additive Mixed Models
Listed in DataCite
We propose an extensive framework for additive regression models for correlated functional responses, allowing for multiple partially nested or crossed functional random effects with flexible correlation structures for, e.g., spatial, temporal, or longitudinal functional data.
Description
Additionally, our framework includes linear and nonlinear effects of functional and scalar covariates that may vary smoothly over the index of the functional response.
It accommodates densely or sparsely observed functional responses and predictors which may be observed with additional error and includes both spline-based and functional principal component-based terms. Estimation and inference in this framework is based on standard additive mixed models, allowing us to take advantage of established methods and robust, flexible algorithms. We provide easy-to-use open source software in the pffr() function for the R-package refund.
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Simulations show that the proposed method recovers relevant effects reliably, handles small sample sizes well and also scales to larger data sets. Applications with spatially and longitudinally observed functional data demonstrate the flexibility in modeling and interpretability of results of our approach.
Links
Where it is published
- Repository landing page tandf.figshare.com/articles/dataset/Functional_Additive_Mixed_Models/987098/1 ↗
landing page · from DataCite
- DOI doi.org/10.6084/m9.figshare.987098.v1 ↗
DOI / persistent id · from DataCite
Documentation and papers
- Creative Commons Attribution 4.0 International creativecommons.org/licenses/by/4.0/legalcode ↗
license · from DataCite
- IsSupplementTo 10.1080/10618600.2014.901914 doi.org/10.1080/10618600.2014.901914 ↗
publication · from DataCite
Catalogue records · 2
- DataCite API api.datacite.org/dois/10.6084/m9.figshare.987098.v1 ↗
metadata API · from DataCite
- DataCite Commons commons.datacite.org/doi.org/10.6084/m9.figshare.987098.v1 ↗
catalogue entry · from DataCite
Topics
- Stated by source
- Biological sciences · Mathematics
- From keywords
- Ecology · Life Sciences · Mathematics & Statistics
- Inferred from text
- Longitudinal study 65%
Related
- Has versionFunctional Additive Mixed Models
- Possibly the same asFunctional Additive Mixed Models
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| DataCite | 10.6084/m9.figshare.987098.v1 | 14 d ago | JSON v1 |
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|---|---|---|---|
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| concepts[field].fos:biological-sciences | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].fos:mathematics | source · DataCite | connector:datacite@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Biological Sciences'] |
| concepts[field].local:field:mathematics-statistics | mapping · DataCite | vocabulary-mapper@1.0.0 | keywords['Mathematics'] |
| concepts[method].local:method:longitudinal-study | enrichment · DataCite | keyword-concept-rules@1.0.0 | title+description (65%) |
| created_date | source · DataCite | connector:datacite@1.0.0 | |
| description | source · DataCite | connector:datacite@1.0.0 | /data/attributes/descriptions |
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| publication_date | source · DataCite | connector:datacite@1.0.0 | /data/attributes/dates |
| title | source · DataCite | connector:datacite@1.0.0 | /data/attributes/titles/0/title |
| updated_date | source · DataCite | connector:datacite@1.0.0 |