Bayesian spatial modeling using random Fourier frequencies
Spectral methods are important for both theory and computation in spatial data analysis.
When data lie on a grid, spectral approaches can take advantage of the discrete Fourier …
When data lie on a grid, spectral approaches can take advantage of the discrete Fourier …
A spatial copula interpolation in a random field with application in air pollution data
Interpolating a skewed conditional spatial random field with missing data is cumbersome in
the absence of Gaussianity assumptions. Copulas can capture different types of joint tail …
the absence of Gaussianity assumptions. Copulas can capture different types of joint tail …
Spatial Cluster-based Copula Model to Interpolate Skewed Conditional Spatial Random Field
D Thakur, I Das, S Chakravarty - arXiv preprint arXiv:2205.13024, 2022 - arxiv.org
Interpolating a skewed conditional spatial random field with missing data is cumbersome in
the absence of Gaussianity assumptions. Maintaining spatial homogeneity and continuity …
the absence of Gaussianity assumptions. Maintaining spatial homogeneity and continuity …