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Geometrical Functionality of the 'spatstat' Family
Defines spatial data types and supports geometrical operations on them. Data types include point patterns, windows (domains), pixel images, line segment patterns, tessellations and hyperframes. Capabilities include creation and manipulation of data (using command line or graphical interaction), plotting, geometrical operations (rotation, shift, rescale, affine transformation), convex hull, discretisation and pixellation, Dirichlet tessellation, Delaunay triangulation, pairwise distances, nearest-neighbour distances, distance transform, morphological operations (erosion, dilation, closing, opening), quadrat counting, geometrical measurement, geometrical covariance, colour maps, calculus on spatial domains, Gaussian blur, level sets of images, transects of images, intersections between objects, minimum distance matching. (Excludes spatial data on a network, which are supported by the package 'spatstat.linnet'.)
Utility Functions for 'spatstat'
Contains utility functions for the 'spatstat' family of packages which may also be useful for other purposes.
Turner Miscellaneous
Miscellaneous utility functions for data manipulation, data tidying, and working with gene expression data.
Random Generation Functionality for the 'spatstat' Family
Functionality for random generation of spatial data in the 'spatstat' family of packages. Generates random spatial patterns of points according to many simple rules (complete spatial randomness, Poisson, binomial, random grid, systematic, cell), randomised alteration of patterns (thinning, random shift, jittering), simulated realisations of random point processes including simple sequential inhibition, Matern inhibition models, Neyman-Scott cluster processes (using direct, Brix-Kendall, or hybrid algorithms), log-Gaussian Cox processes, product shot noise cluster processes and Gibbs point processes (using Metropolis-Hastings birth-death-shift algorithm, alternating Gibbs sampler, or coupling-from-the-past perfect simulation). Also generates random spatial patterns of line segments, random tessellations, and random images (random noise, random mosaics). Excludes random generation on a linear network, which is covered by the separate package 'spatstat.linnet'.
Turn Vectors and Lists of Vectors into Indexed Structures
Package designed for working with vectors and lists of vectors, mainly for turning them into other indexed data structures.
1000 Genomes Project Metadata
Metadata about populations and data about samples from the 1000 Genomes Project, including the 2,504 samples sequenced for the Phase 3 release and the expanded collection of 3,202 samples with 602 additional trios. The data is described in Auton et al. (2015)
Vector Field Visualizations with 'ggplot2'
A 'ggplot2' extension for visualizing vector fields in two-dimensional space. Provides flexible tools for creating vector and stream field layers, visualizing gradients and potential fields, and smoothing vector and scalar data to estimate underlying patterns.
Extended Generalised Linear Hidden Markov Models
Fits a variety of hidden Markov models, structured
in an extended generalized linear model framework. See
T. Rolf Turner, Murray A. Cameron, and Peter J. Thomson
(1998)
Utilities for SNP-Based Kinship Analysis
Utilities for single nucleotide polymorphism (SNP) based kinship analysis
testing and evaluation. The 'skater' package contains functions for importing, parsing,
and analyzing pedigree data, performing relationship degree inference, benchmarking
relationship degree classification, and summarizing identity by descent (IBD) segment data.
Package functions and methods are described in Turner et al. (2021) "skater: An R package
for SNP-based Kinship Analysis, Testing, and Evaluation"
Various Plotting Functions
Lots of plots, various labeling, axis and color scaling functions. The author/maintainer died in September 2023.