Fits a spatially discrete approximation to a log-Gaussian Cox process
    model for spatially aggregated disease count data, estimated by Monte Carlo
    Maximum Likelihood as in Christensen (2004) <doi:10.1198/106186004X2525> and
    Johnson, Diggle and Giorgi (2019) <doi:10.1002/sim.8339>. Performance-critical
    steps (aggregated correlation assembly, Metropolis-adjusted Langevin
    algorithm (MALA) sampling, the Monte Carlo likelihood, and the
    Kronecker-structured space-time likelihood) are implemented in
    C++ via 'RcppArmadillo'. Provides a one-line, 'glm'-like interface and
    statistical extensions including a nugget term, general 'Matern' smoothness,
    raster and misaligned covariates, restricted spatial regression,
    importance-sampling diagnostics and re-anchored Monte Carlo maximum
    likelihood (MCML).

Data sets and functions to support the books "Statistics: Data 
        analysis and modelling" by Speekenbrink, M. (2021) 
        <https://mspeekenbrink.github.io/sdam-book/> and "An R companion to 
        Statistics: data analysis and modelling" by Speekenbrink, M. (2021) 
        <https://mspeekenbrink.github.io/sdam-r-companion/>. All datasets 
        analysed in these books are provided in this package. In addition, the 
        package provides functions to compute sample statistics (variance, 
        standard deviation, mode), create raincloud and enhanced Q-Q plots, and 
        expand Anova results into omnibus tests and tests of individual 
        contrasts.

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, 
    gamma ray logs) (Johnson, 1992, <ISSN 0037-0738>).