diff --git a/DESCRIPTION b/DESCRIPTION index f7a501c..c83588d 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -8,7 +8,7 @@ Authors@R: c( person("Matthew", "Sainsbury-Dale", , "msdale@uow.edu.au", c("aut"))) Maintainer: Andrew Zammit-Mangion VignetteBuilder: knitr -Description: A tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach models the field, and hence the covariance function, using a set of basis functions. This fixed-rank basis-function representation facilitates the modelling of big data, and the method naturally allows for non-stationary, anisotropic covariance functions. Discretisation of the spatial domain into so-called basic areal units (BAUs) facilitates the use of observations with varying support (i.e., both point-referenced and areal supports, potentially simultaneously), and prediction over arbitrary user-specified regions. `FRK` also supports inference over various manifolds, including the 2D plane and 3D sphere, and it provides helper functions to model, fit, predict, and plot with relative ease. Version 2.0.0 and above also supports the modelling of non-Gaussian data (e.g., Poisson, binomial, negative-binomial, gamma, and inverse-Gaussian) by employing a generalised linear mixed model (GLMM) framework. Zammit-Mangion and Cressie describe `FRK` in a Gaussian setting, and detail its use of basis functions and BAUs, while Sainsbury-Dale et al. describe `FRK` in a non-Gaussian setting; two vignettes are available that summarise these papers and provide additional examples. +Description: A tool for spatial/spatio-temporal modelling and prediction with large datasets. The approach models the field, and hence the covariance function, using a set of basis functions. This fixed-rank basis-function representation facilitates the modelling of big data, and the method naturally allows for non-stationary, anisotropic covariance functions. Discretisation of the spatial domain into so-called basic areal units (BAUs) facilitates the use of observations with varying support (i.e., both point-referenced and areal supports, potentially simultaneously), and prediction over arbitrary user-specified regions. `FRK` also supports inference over various manifolds, including the 2D plane and 3D sphere, and it provides helper functions to model, fit, predict, and plot with relative ease. Version 2.0.0 and above also supports the modelling of non-Gaussian data (e.g., Poisson, binomial, negative-binomial, gamma, and inverse-Gaussian) by employing a generalised linear mixed model (GLMM) framework. Zammit-Mangion and Cressie describe `FRK` in a Gaussian setting, and detail its use of basis functions and BAUs, while Sainsbury-Dale, Zammit-Mangion, and Cressie describe `FRK` in a non-Gaussian setting; two vignettes are available that summarise these papers and provide additional examples. URL: https://andrewzm.github.io/FRK/, https://github.com/andrewzm/FRK/ BugReports: https://github.com/andrewzm/FRK/issues/ Depends: diff --git a/R/SRE.R b/R/SRE.R index 9044024..c7e70d5 100644 --- a/R/SRE.R +++ b/R/SRE.R @@ -278,7 +278,7 @@ #' @references #' Zammit-Mangion, A. and Cressie, N. (2021). FRK: An R package for spatial and spatio-temporal prediction with large datasets. Journal of Statistical Software, 98(4), 1-48. doi:10.18637/jss.v098.i04. #' -#' Sainsbury-Dale, M. and Zammit-Mangion, A. and Cressie, N. (2023) Modelling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data using FRK, arXiv:2110.02507 +#' Sainsbury-Dale, M. and Zammit-Mangion, A. and Cressie, N. (2024) Modelling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data using FRK. Journal of Statistical Software, 108(10), 1--39. doi:10.18637/jss.v108.i10. #' @export #' @examples #' library("FRK") diff --git a/inst/CITATION b/inst/CITATION index 85168a1..a97d7cf 100644 --- a/inst/CITATION +++ b/inst/CITATION @@ -1,30 +1,32 @@ -bibentry( - bibtype = "Article", - title = "FRK: an R package for spatial and spatio-temporal prediction with large datasets", - author = c(person("Andrew Zammit-Mangion"), person("Noel Cressie")), - journal = "Journal of Statistical Software", - year = "2021", - volume = "98", - number = "4", - pages = "1--48", - header = "To cite FRK version 1 (with EM algorithm) in publications use:", - textVersion = paste( - "Zammit-Mangion A, Cressie N (2021).", - "FRK: an R package for spatial and spatio-temporal prediction with large datasets.", - "Journal of Statistical Software, 98(4), 1–48." - ) +bibentry(bibtype = "Article", + title = "{FRK}: An {R} Package for Spatial and Spatio-Temporal Prediction with Large Datasets", + author = c(person(given = "Andrew", + family = "Zammit-Mangion"), + person(given = "Noel", + family = "Cressie")), + journal = "Journal of Statistical Software", + year = "2021", + volume = "98", + number = "4", + pages = "1--48", + doi = "10.18637/jss.v098.i04", + header = "To cite FRK version 1 (with EM algorithm) in publications use:", ) - -bibentry( - bibtype = "Article", - title = "Modelling big, heterogeneous, non-Gaussian spatial and spatio-temporal data using FRK", - author = c(person("Matthew Sainsbury-Dale"), person("Andrew Zammit-Mangion"), person("Noel Cressie")), - journal = "arXiv:2110.02507", - year = "2022", - header = "To cite FRK version 2 (non-Gaussian data) in publications use:", textVersion = paste( - "Sainsbury-Dale M, Zammit-Mangion A, Cressie N (2022).", - "Modelling big, heterogeneous, non-Gaussian spatial and spatio-temporal data using FRK", - "arXiv:2110.02507" - ) +bibentry(bibtype = "Article", + title = "Modeling Big, Heterogeneous, Non-{G}aussian Spatial and Spatio-Temporal Data Using {FRK}", + author = c(person(given = "Matthew", + family = "Sainsbury-Dale", + email = "msdale@uow.edu.au"), + person(given = "Andrew", + family = "Zammit-Mangion"), + person(given = "Noel", + family = "Cressie")), + journal = "Journal of Statistical Software", + year = "2024", + volume = "108", + number = "10", + pages = "1--39", + doi = "10.18637/jss.v108.i10", + header = "To cite FRK version 2 (non-Gaussian data) in publications use:" ) diff --git a/man/SRE.Rd b/man/SRE.Rd index 80649f9..e3c79fa 100644 --- a/man/SRE.Rd +++ b/man/SRE.Rd @@ -451,7 +451,7 @@ ggpubr::ggarrange(plotlist = plotlist, nrow = 1, align = "hv", legend = "top")} \references{ Zammit-Mangion, A. and Cressie, N. (2021). FRK: An R package for spatial and spatio-temporal prediction with large datasets. Journal of Statistical Software, 98(4), 1-48. doi:10.18637/jss.v098.i04. -Sainsbury-Dale, M. and Zammit-Mangion, A. and Cressie, N. (2023) Modelling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data using FRK, arXiv:2110.02507 +Sainsbury-Dale, M. and Zammit-Mangion, A. and Cressie, N. (2024) Modelling Big, Heterogeneous, Non-Gaussian Spatial and Spatio-Temporal Data using FRK. Journal of Statistical Software, 108(10), 1--39. doi:10.18637/jss.v108.i10. } \seealso{ \code{\link{SRE-class}} for details on the SRE object internals,