Bayesian Nonstationary and Nonparametric Covariance Estimation for Large Spatial Data

  title={Bayesian Nonstationary and Nonparametric Covariance Estimation for Large Spatial Data},
  author={Brian Kidd and Matthias Katzfuss},
  journal={arXiv: Methodology},
In spatial statistics, it is often assumed that the spatial field of interest is stationary and its covariance has a simple parametric form, but these assumptions are not appropriate in many applications. Given replicate observations of a Gaussian spatial field, we propose nonstationary and nonparametric Bayesian inference on the spatial dependence. Instead of estimating the quadratic (in the number of spatial locations) entries of the covariance matrix, the idea is to infer a near-linear… Expand

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