Package: ldmppr
Type: Package
Title: Estimate and Simulate from Location Dependent Marked Point
        Processes
Version: 1.1.3
Authors@R: c(
  person("Lane", "Drew", role = c("aut", "cre", "cph"), email = "lanetdrew@gmail.com", comment = c(ORCID = "0009-0006-5427-4092")),
  person("Andee", "Kaplan", role = "aut", comment = c(ORCID = "0000-0002-2940-889X")))
Maintainer: Lane Drew <lanetdrew@gmail.com>
Description: A suite of tools for estimating, assessing model fit, simulating from, and visualizing location dependent marked point processes characterized by regularity in the pattern.
    You provide a reference marked point process, a set of raster images containing location specific covariates, and select the estimation algorithm and type of mark model.
    'ldmppr' estimates the process and mark models and allows you to check the appropriateness of the model using a variety of diagnostic tools.
    Once a satisfactory model fit is obtained, you can simulate from the model and visualize the results.
    Documentation for the package 'ldmppr' is available in the form of a vignette.
License: GPL (>= 3)
Encoding: UTF-8
LazyData: true
Imports: stats, bundle, Rcpp (>= 1.0.12), terra, doParallel, xgboost,
        parsnip (>= 1.4.0), dials, recipes, rsample, tune, workflows,
        magrittr, hardhat, ggplot2, spatstat.geom, spatstat.explore,
        nloptr, GET, progress, progressr, future, furrr, foreach,
        yardstick
LinkingTo: Rcpp, RcppArmadillo
URL: https://github.com/lanedrew/ldmppr,
        https://lanedrew.github.io/ldmppr/
BugReports: https://github.com/lanedrew/ldmppr/issues
RoxygenNote: 7.3.3
Suggests: knitr, rmarkdown, testthat (>= 3.0.0), dplyr, rstudioapi,
        parallelly, ranger
VignetteBuilder: knitr
Depends: R (>= 3.5.0)
Config/testthat/edition: 3
NeedsCompilation: yes
Packaged: 2026-03-02 18:21:56 UTC; lanedrew
Author: Lane Drew [aut, cre, cph] (ORCID:
    <https://orcid.org/0009-0006-5427-4092>),
  Andee Kaplan [aut] (ORCID: <https://orcid.org/0000-0002-2940-889X>)
Repository: CRAN
Date/Publication: 2026-03-03 08:50:09 UTC
Built: R 4.7.0; x86_64-w64-mingw32; 2026-04-28 05:32:48 UTC; windows
Archs: x64
