Suggests: testthat (>= 3.0.0), knitr, tidyr, rmarkdown

Title: Spatially Discrete Approximation to Log-Gaussian Cox Processes
person("Olatunji", "Johnson", email = "olatunjijohnson21111@gmail.com", role = c("aut", "cre")),
person("Emanuele", "Giorgi", email = "e.giorgi@lancaster.ac.uk", role = "aut"),
person("Peter", "Diggle", email = "p.diggle@lancaster.ac.uk", role = "aut"))
Description: Provides a computationally efficient discrete approximation to log-Gaussian Cox process model for spatially aggregated disease count data. It uses Monte Carlo Maximum Likelihood for model parameter estimation as proposed by Christensen (2004) <doi: 10.1198/106186004X2525> and delivers prediction of spatially discrete and continuous relative risk.

Description: Provides a computationally efficient discrete approximation to log-Gaussian Cox process model for spatially aggregated disease count data. It uses Monte Carlo Maximum Likelihood for model parameter estimation as proposed by Christensen (2004) <doi: 10.1198/106186004X2525> and delivers prediction of spatially discrete and continuous relative risk. It performs inference for static spatial and spatio-temporal dataset.
methods, spacetime(>= 1.2.2), mapview(>= 2.6.0), geoR(>=

Description: Provides a computationally efficient discrete approximation to log-Gaussian Cox process model for spatially aggregated disease count data. It uses Monte Carlo Maximum Likelihood for model parameter estimation as proposed by Christensen (2004) <doi: 10.1198/106186004X2525> and delivers prediction of spatially discrete and continuous relative risk. It performs inference for static spatial and spatio-temporal dataset. The details of the methods are provided in Johnson et al (2019) <doi:10.1002/sim.8339>.
maptools(>= 0.9.2), progress(>= 1.1.2), methods, spacetime(>=

maptools(>= 1.1-1), progress(>= 1.1.2), methods, spacetime(>=

Authors@R: c(person("John R.", "Ortiz", role = c("aut", "cre"), email = "jrortizt@unal.edu.co"),
person("Carlos", "Jaramillo", role = "aut"),
person("Carlos", "Moreno", role = "ctb"))
Maintainer: John R. Ortiz <jrortizt@unal.edu.co>
Description: A fast, consistent tool for plotting and facilitating the analysis of stratigraphic
and sedimentological data. Taking advantage of the flexible plotting tools available in R,
'SDAR' uses stratigraphic and sedimentological data to produce detailed graphic logs for
outcrop sections and borehole logs. These logs can include multiple features (e.g., bed thickness,
lithology, samples, sedimentary structures, colors, fossil content, bioturbation index,
electrical logs) (Johnson, 1992, <ISSN 0037-0738>).
Imports: methods, grid, linbin, grImport2, readxl
Note: The development of this package was supported by Carlos
Jaramillo, Center for Tropical Paleoecology and Archaeology at