Functions for performing graphical difference testing.     
             Differences are generated between raster images.
             Comparisons can be performed between different package
             versions and between different R versions.

Cross-validated eigenvalues are estimated by
    splitting a graph into two parts, the training and the test graph.
    The training graph is used to estimate eigenvectors, and
    the test graph is used to evaluate the correlation between the training
    eigenvectors and the eigenvectors of the test graph.
    The correlations follow a simple central limit theorem that can
    be used to estimate graph dimension via hypothesis testing, see
    Chen et al. (2021) <arXiv:2108.03336> for details.

A set of psychometric tools for cognitive diagnosis modeling based on the generalized deterministic inputs, noisy and gate (G-DINA) model by de la Torre (2011) <DOI:10.1007/s11336-011-9207-7> and its extensions, including the sequential G-DINA model by Ma and de la Torre (2016) <DOI:10.1111/bmsp.12070> for polytomous responses, and the polytomous G-DINA model by Chen and de la Torre <DOI:10.1177/0146621613479818> for polytomous attributes. Joint attribute distribution can be independent, saturated, higher-order, loglinear smoothed or structured. Q-matrix validation, item and model fit statistics, model comparison at test and item level and differential item functioning can also be conducted. A graphical user interface is also provided. For tutorials, please check Ma and de la Torre (2020) <DOI:10.18637/jss.v093.i14>, Ma and de la Torre (2019) <DOI:10.1111/emip.12262>, Ma (2019) <DOI:10.1007/978-3-030-05584-4_29> and de la Torre and Akbay (2019).

Provides classes and functions to calculate various 
             distance measures and routes in heterogeneous geographic 
             spaces represented as grids. The package implements measures
             to model dispersal histories first presented by van Etten and
             Hijmans (2010) <doi:10.1371/journal.pone.0012060>. Least-cost
             distances as well as more complex distances based on (constrained)
             random walks can be calculated. The distances implemented in 
             the package are used in geographical genetics, accessibility 
             indicators, and may also have applications in other fields of
             geospatial analysis.