Quadrangle Mesh

Create surface forms from matrix or 'raster' data for flexible plotting and conversion to other mesh types. The functions 'quadmesh' or 'triangmesh' produce a continuous surface as a 'mesh3d' object as used by the 'rgl' package. This is used for plotting raster data in 3D (optionally with texture), and allows the application of a map projection without data loss and many processing applications that are restricted by inflexible regular grid rasters. There are discrete forms of these continuous surfaces available with 'dquadmesh' and 'dtriangmesh' functions.

Raster Georeferencing, Grid Affine Transforms, Cell Abstraction

Tools for raster georeferencing, grid affine transforms, and general raster logic. These functions provide converters between raster specifications, world vector, geotransform, 'RasterIO' window, and 'RasterIO window' in 'sf' package list format. There are functions to offset a matrix by padding any of four corners (useful for vectorizing neighbourhood operations), and helper functions to harvesting user clicks on a graphics device to use for simple georeferencing of images. Methods used are available from < https://en.wikipedia.org/wiki/World_file> and < https://gdal.org/user/raster_data_model.html>.

Tools for Standardizing Variables for Regression in R

Tools which allow regression variables to be placed on similar scales, offering computational benefits as well as easing interpretation of regression output.

Tools for 'ROMS' the Regional Ocean Modeling System

Helper functions for working with Regional Ocean Modeling System 'ROMS' output. See < https://www.myroms.org/> for more information about 'ROMS'.

Meridional and Parallel Lines for Maps

Create graticule lines and labels for maps. Control the creation of lines or tiles by setting their placement (at particular meridians and parallels) and extent (along parallels and meridians). Labels are created independently of lines.

Weighted Descriptive Statistics

Weighted versions of common descriptive statistics (variance, standard deviation, covariance, correlation, quantiles).

Constrained Triangulation for Simple Features

Build a constrained high quality Delaunay triangulation from simple features objects, applying constraints based on input line segments, and triangle properties including maximum area, minimum internal angle. The triangulation code in 'RTriangle' uses the method of Cheng, Dey and Shewchuk (2012, ISBN:9781584887300). For a low-dependency alternative with low-quality path-based constrained triangulation see < https://CRAN.R-project.org/package=decido> and for high-quality configurable triangulation see < https://github.com/hypertidy/anglr>. Also consider comparison with the 'GEOS' lib which since version 3.10.0 includes a low quality polygon triangulation method that starts with ear clipping and refines to Delaunay.

Convolution-Based Nonstationary Spatial Modeling

Fits convolution-based nonstationary Gaussian process models to point-referenced spatial data. The nonstationary covariance function allows the user to specify the underlying correlation structure and which spatial dependence parameters should be allowed to vary over space: the anisotropy, nugget variance, and process variance. The parameters are estimated via maximum likelihood, using a local likelihood approach. Also provided are functions to fit stationary spatial models for comparison, calculate the Kriging predictor and standard errors, and create various plots to visualize nonstationarity.

Spatial Extent Tools

Functions to produce a fully fledged 'geo-spatial' object extent as a 'SpatialPolygonsDataFrame'. Also included are functions to generate polygons from raster data using 'quadmesh' techniques, a round number buffered extent, and general spatial-extent and 'raster-like' extent helpers missing from the originating packages. Some latitude-based tools for polar maps are included.

Composite Scoring via Principal Component Analysis of Ridit Scores

Implements 'PRIDIT' (Principal Component Analysis applied to 'RIDITs'), an unsupervised, nonparametric method for aggregating ordinal, categorical, and continuous indicators into a single interpretable composite score. Originally proposed by Brockett et al. (2002) for insurance fraud detection and extended to hospital quality measurement by Lieberthal (2008) and Lieberthal and Comer (2013) . The package provides: (1) low-level functions ridit(), PRIDITweight(), and PRIDITscore(); (2) a unified pridit() entry point returning a classed object with print, summary, 'autoplot', and 'coef' methods; (3) pridit_boot() for bootstrap confidence intervals on scores and weights; (4) a step_pridit() recipe step for out-of-sample scoring within the 'tidymodels' framework; and (5) pridit_longitudinal() for panel data, computing cross-period stability of scores and weights.