Corpus ID: 219559280

A functional-data approach to the Argo data

@article{Yarger2020AFA,
  title={A functional-data approach to the Argo data},
  author={Drew Yarger and Stilian A. Stoev and Tailen Hsing},
  journal={arXiv: Applications},
  year={2020}
}
The Argo data is a modern oceanography dataset that provides unprecedented global coverage of temperature and salinity measurements in the upper 2,000 meters of depth of the ocean. We study the Argo data from the perspective of functional data analysis (FDA). We develop spatio-temporal functional kriging methodology for mean and covariance estimation to predict temperature and salinity at a fixed location as a smooth function of depth. By combining tools from FDA and spatial statistics… Expand
Spatio-temporal Local Interpolation of Global Ocean Heat Transport using Argo Floats: A Debiased Latent Gaussian Process Approach
The world ocean plays a key role in redistributing heat in the climate system and hence in regulating Earth’s climate. Yet statistical analysis of ocean heat transport suffers from partiallyExpand
Inference and Computation for Sparsely Sampled Random Surfaces
Non-parametric inference for functional data over two-dimensional domains entails additional computational and statistical challenges, compared to the one-dimensional case. Separability of theExpand

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