Package: rts2
Title: Log-Gaussian Cox Process Models with Approximations
Version: 1.0.4
Date: 2026-07-19
Authors@R: 
    person(given = "Sam",
           family = "Watson",
           role = c("aut", "cre"),
           email = "s.i.watson@bham.ac.uk",
           comment = c(ORCID = "0000-0002-8972-769X"))
Description: Supports modelling case data to facilitate. The package
        provides automated computational grid generation over an area
        of interest with methods to map covariates between geographies,
        model fitting including spatially aggregated case counts, and
        predictions and visualisation. Monte Carlo maximum likelihood
        is the main fitting method with a low-rank approximation for
        Gaussian processes described by Solin and Särkkä (2020)
        <doi:10.1007/s11222-019-09886-w> and a stochastic partial
        differential equation approximation. Bayesian methods are also
        provided for some methods. Log-Gaussian Cox Processes are
        described by Diggle et al. (2013) <doi:10.1214/13-STS441>.
License: CC BY-SA 4.0
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.3.3
Biarch: true
Depends: R (>= 3.5.0), sf (>= 1.0-14)
Imports: methods, R6, Rcpp (>= 0.12.0), RcppParallel (>= 5.0.1), rstan
        (>= 2.30.0), rstantools (>= 2.1.1), lubridate (>= 1.9.0), stars
        (>= 0.6-1), raster (>= 3.6-1), glmmrBase (>= 1.3.0), spdep,
        fmesher, FNN, quadprog
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0),
        RcppParallel (>= 5.0.1), rstan (>= 2.30.0), StanHeaders (>=
        2.32.0), glmmrBase (>= 1.3.0)
SystemRequirements: GNU make
NeedsCompilation: yes
Packaged: 2026-07-19 17:48:55 UTC; root
Author: Sam Watson [aut, cre] (ORCID:
        <https://orcid.org/0000-0002-8972-769X>)
Maintainer: Sam Watson <s.i.watson@bham.ac.uk>
Config/pak/sysreqs: libabsl-dev cmake libgdal-dev gdal-bin libgeos-dev
        make libssl-dev libproj-dev libsqlite3-dev libudunits2-dev
Repository: https://samueliwatson.r-universe.dev
Date/Publication: 2026-07-19 15:20:02 UTC
RemoteUrl: https://github.com/cran/rts2
RemoteRef: HEAD
RemoteSha: 69f31970be48e4847bf984040a3fdd91425e6474