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spate

Spatio-Temporal Modeling of Large Data Using a Spectral SPDE Approach

v1.7.5 · Oct 3, 2023 · GPL-2

Description

Functionality for spatio-temporal modeling of large data sets is provided. A Gaussian process in space and time is defined through a stochastic partial differential equation (SPDE). The SPDE is solved in the spectral space, and after discretizing in time and space, a linear Gaussian state space model is obtained. When doing inference, the main computational difficulty consists in evaluating the likelihood and in sampling from the full conditional of the spectral coefficients, or equivalently, the latent space-time process. In comparison to the traditional approach of using a spatio-temporal covariance function, the spectral SPDE approach is computationally advantageous. See Sigrist, Kuensch, and Stahel (2015) <doi:10.1111/rssb.12061> for more information on the methodology. This package aims at providing tools for two different modeling approaches. First, the SPDE based spatio-temporal model can be used as a component in a customized hierarchical Bayesian model (HBM). The functions of the package then provide parameterizations of the process part of the model as well as computationally efficient algorithms needed for doing inference with the HBM. Alternatively, the adaptive MCMC algorithm implemented in the package can be used as an algorithm for doing inference without any additional modeling. The MCMC algorithm supports data that follow a Gaussian or a censored distribution with point mass at zero. Covariates can be included in the model through a regression term.

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CRAN incoming feasibility

Maintainer: ‘Fabio Sigrist <fabiosigrist@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Fabio",
                      family = "Sigrist",
                      role = c("aut", "cre"),
                      email = "fabiosigrist@gmail.com"),
               person(given = c("Hans", "R."),
                      family = "Kuensch",
                      role = "aut"),
               person(given = c("Werner", "A."),
                      family = "Stahel",
                      role = "aut"))
as necessary.
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Fabio Sigrist <fabiosigrist@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Fabio",
                      family = "Sigrist",
                      role = c("aut", "cre"),
                      email = "fabiosigrist@gmail.com"),
               person(given = c("Hans", "R."),
                      family = "Kuensch",
                      role = "aut"),
               person(given = c("Werner", "A."),
                      family = "Stahel",
                      role = "aut"))
as necessary.
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NOTE 12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE Mar 9, 2026
NOTE r-devel-linux-x86_64-debian-clang

CRAN incoming feasibility

Maintainer: ‘Fabio Sigrist <fabiosigrist@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Fabio",
                      family = "Sigrist",
                      role = c("aut", "cre"),
                      email = "fabiosigrist@gmail.com"),
               person(given = c("Hans", "R."),
                      family = "Kuensch",
                      role = "aut"),
               person(given = c("Werner", "A."),
                      fami
NOTE r-devel-linux-x86_64-debian-gcc

CRAN incoming feasibility

Maintainer: ‘Fabio Sigrist <fabiosigrist@gmail.com>’

No Authors@R field in DESCRIPTION.
Please add one, modifying
  Authors@R: c(person(given = "Fabio",
                      family = "Sigrist",
                      role = c("aut", "cre"),
                      email = "fabiosigrist@gmail.com"),
               person(given = c("Hans", "R."),
                      family = "Kuensch",
                      role = "aut"),
               person(given = c("Werner", "A."),
                      fami

Dependency Network

Dependencies Reverse dependencies mvtnorm truncnorm spate

Version History

new 1.7.5 Mar 9, 2026