Fast moment-based hierarchical model fitting. Implements
    methods from the papers
    "Fast Moment-Based Estimation for Hierarchical Models," by Perry (2017)
    and
    "Fitting a Deeply Nested Hierarchical Model to a Large Book Review
    Dataset Using a Moment-Based Estimator," by Zhang, Schmaus, and Perry
    (2018).

Modern model-based geostatistics for point-referenced data. This package provides a
    simple interface to run spatial machine learning models and geostatistical models
    that estimate a continuous (raster) surface from point-referenced outcomes and,
    optionally, a set of raster covariates. The package also includes functions to
    summarize raster outcomes by (polygon) region while preserving uncertainty.

Provides an interactive 'shiny' application for teaching and applied
    analysis of geostatistical data. Users can explore spatial data, assess
    spatial correlation through the empirical variogram, fit model-based
    geostatistical models for continuous, prevalence and count outcomes, produce
    spatial predictions, and download reports. The methodology follows the
    model-based geostatistics framework of Diggle and Giorgi (2019, ISBN:9781138732353).

Provides spatially survey balanced designs using the quasi-random number method described Robinson et al. (2013) <doi:10.1111/biom.12059> and adjusted in Robinson et al. (2017) <doi:10.1016/j.spl.2017.05.004>. Designs using MBHdesign can: 1) accommodate, without substantial detrimental effects on spatial balance, legacy sites (Foster et al., 2017 <doi:10.1111/2041-210X.12782>); 2) be based on points or transects (foster et al. 2020 <doi:10.1111/2041-210X.13321> and produce clustered samples (Foster et al. (in press). Additional information about the package use itself is given in Foster (2021) <doi:10.1111/2041-210X.13535>.

Allows practitioners and researchers a wholesale approach for deriving magnitude-based inferences from raw data. A major goal of 'mbir' is to programmatically detect appropriate statistical tests to run in lieu of relying on practitioners to determine correct stepwise procedures independently.