Package: stelfi
Type: Package
Title: Hawkes and Log-Gaussian Cox Point Processes Using Template Model
        Builder
Version: 1.0.2
Date: 2025-09-15
Authors@R: 
  c(person(given = "Charlotte M.",
           family = "Jones-Todd",
           role = c("aut", "cre", "cph"),
           email = "c.jonestodd@auckland.ac.nz",
           comment = c(ORCID = "0000-0003-1201-2781",
	   "Charlotte Jones-Todd wrote and continued developmend of the main code.")),
    person(given  = "Alec",
           family = "van Helsdingen",
           role = "aut",
	   comment = "Alec van Helsdingen wrote the Hawkes templates and extended self-exciting TMB templates"),
    person(given = "Xiangjie",
           family = "Xue",
           role = "ctb",
	   comment = "Xiangjie Xue worked the early spatio-temporal self-exciting TMB templates"),
     person(given = "Joseph",
           family = "Reps",
           role = "ctb",
	   comment = "Joseph Reps worked on the spatio-temporal self-exciting TMB templates"),	   
    person(given = "Marsden Fund",
           family = "3723517",
           role = "fnd"),
    person(given = "Asian Office of Aerospace Research & Development",
           family = "FA2386-21-1-4028",
           role = "fnd"))
Depends: R (>= 4.5.0)
Imports: TMB (>= 1.9.6), sf (>= 1.0.14), fmesher, Matrix, ggplot2 (>=
        3.4.3), dplyr (>= 1.1.3), gridExtra (>= 2.3), tidyr (>= 1.3.1)
LinkingTo: TMB, RcppEigen
Description: Fit Hawkes and log-Gaussian Cox process models with
        extensions. Introduced in Hawkes (1971) <doi:10.2307/2334319> a
        Hawkes process is a self-exciting temporal point process where
        the occurrence of an event immediately increases the chance of
        another. We extend this to consider self-inhibiting process and
        a non-homogeneous background rate. A log-Gaussian Cox process
        is a Poisson point process where the log-intensity is given by
        a Gaussian random field. We extend this to a joint likelihood
        formulation fitting a marked log-Gaussian Cox model. In
        addition, the package offers functionality to fit self-exciting
        spatiotemporal point processes. Models are fitted via maximum
        likelihood using 'TMB' (Template Model Builder). Where included
        1) random fields are assumed to be Gaussian and are integrated
        over using the Laplace approximation and 2) a stochastic
        partial differential equation model, introduced by Lindgren,
        Rue, and Lindström. (2011)
        <doi:10.1111/j.1467-9868.2011.00777.x>, is defined for the
        field(s).
License: GPL (>= 3)
URL: https://github.com/cmjt/stelfi/
BugReports: https://github.com/cmjt/stelfi/issues
LazyData: TRUE
LazyDataCompression: xz
Encoding: UTF-8
RoxygenNote: 7.3.3
Suggests: testthat (>= 3.1.10), rmarkdown, parallel, spatstat.utils,
        spatstat.geom, hawkesbow, covr, knitr
Config/testthat/edition: 3
VignetteBuilder: knitr
Config/pak/sysreqs: libabsl-dev cmake libgdal-dev gdal-bin libgeos-dev
        libicu-dev libssl-dev libproj-dev libsqlite3-dev
        libudunits2-dev
Repository: https://cmjt.r-universe.dev
Date/Publication: 2025-09-15 01:54:21 UTC
RemoteUrl: https://github.com/cmjt/stelfi
RemoteRef: HEAD
RemoteSha: 5b989108bc6900d2665160e73913fb3ddf07a262
NeedsCompilation: yes
Packaged: 2026-06-13 06:29:00 UTC; root
Author: Charlotte M. Jones-Todd [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0003-1201-2781>, Charlotte Jones-Todd wrote
    and continued developmend of the main code.),
  Alec van Helsdingen [aut] (Alec van Helsdingen wrote the Hawkes
    templates and extended self-exciting TMB templates),
  Xiangjie Xue [ctb] (Xiangjie Xue worked the early spatio-temporal
    self-exciting TMB templates),
  Joseph Reps [ctb] (Joseph Reps worked on the spatio-temporal
    self-exciting TMB templates),
  Marsden Fund 3723517 [fnd],
  Asian Office of Aerospace Research & Development FA2386-21-1-4028 [fnd]
Maintainer: Charlotte M. Jones-Todd <c.jonestodd@auckland.ac.nz>