Debian GIS Statistics packages

This GNU R package calculates the Delaunay triangulation and the Dirichlet or Voronoi tessellation (with respect to the entire plane) of a planar point set. This package is used in Spatial Point Pattern analysis, model-fitting and simulation as it is done for instance in the package r-cran-spatstat.

For curve, surface and function fitting with an emphasis on splines, spatial data and spatial statistics. The major methods include cubic, and thin plate splines, Kriging and compact covariances for large data sets. The splines and Kriging methods are supported by functions that can determine the smoothing parameter (nugget and sill variance) and other covariance parameters by cross validation and also by restricted maximum likelihood. For Kriging there is an easy to use function that also estimates the correlation scale (range). A major feature is that any covariance function implemented in R and following a simple fields format can be used for spatial prediction. There are also many useful functions for plotting and working with spatial data as images. This package also contains an implementation of sparse matrix methods for large spatial data sets.

This GNU R package provides spatio-temporal geostatistical modelling, prediction and Simulation Variogram modelling; simple, ordinary and universal point or block (co)kriging; spatio-temporal kriging; sequential Gaussian or indicator (co)simulation; variogram and variogram map plotting utility functions; supports sf and stars.

This package provides facilities for easily producing high-resolution maps based on data sets in the GNU R statistical computing environment. It includes high-resolution map data for the entire world, along with maps of China (including provincial boundaries) and a higher-resolution map of New Zealand and a number of nearby Pacific islands.

The suggested r-cran-mapproj package adds facilities for calculating geographic projections, which are used by mapmakers to compensate for the inaccuracies inherent in projecting a spheroid's surface onto a two-dimensional plane.

This package provides facilities for easily producing cartographic projections of maps based on data sets in the GNU R statistical computing environment. Projections are used by mapmakers to compensate for the inaccuracies inherent in projecting a spheroid's surface onto a two-dimensional plane.

This package provides facilities for easily producing maps based on data sets in the GNU R statistical computing environment.

The r-cran-maps package includes map data for the United States (including state and county-level maps), New Zealand, and a world map; additional maps (including a higher-resolution world map) are available in the suggested r-cran-mapdata package.

The suggested r-cran-mapproj package adds facilities for calculating geographic projections, which are used by mapmakers to compensate for the inaccuracies inherent in projecting a spheroid's surface onto a two-dimensional plane.

This GNU R package provides functions for reading, writing, manipulating, analyzing and modeling of gridded spatial data. The package implements basic and high-level functions. Processing of very large files is supported.

This GNU R package provides classes and methods for spatial data. The classes document where the spatial location information resides, for 2D or 3D data. Utility functions are provided, e.g. for plotting data as maps, spatial selection, as well as methods for retrieving coordinates, for subsetting, print, summary, etc.

A GNU R package for analysing spatial data, mainly Spatial Point Patterns, including multitype/marked points and spatial covariates, in any two-dimensional spatial region. Contains functions for plotting spatial data, exploratory data analysis, model-fitting, simulation, spatial sampling, model diagnostics, and formal inference. Data types include point patterns, line segment patterns, spatial windows, and pixel images. Point process models can be fitted to point pattern data. Cluster type models are fitted by the method of minimum contrast. Very general Gibbs point process models can be fitted to point pattern data using a function ppm similar to lm or glm. Models may include dependence on covariates, interpoint interaction and dependence on marks. Fitted models can be simulated automatically. Also provides facilities for formal inference (such as chi-squared tests) and model diagnostics (including simulation envelopes, residuals, residual plots and Q-Q plots).

A collection of functions to create spatial weights matrix objects from polygon contiguities, from point patterns by distance and tessellations, for summarizing these objects, and for permitting their use in spatial data analysis, including regional aggregation by minimum spanning tree; a collection of tests for spatial autocorrelation, including global Moran's I, APLE, Geary's C, Hubert/Mantel general cross product statistic, Empirical Bayes estimates and Assunção/Reis Index, Getis/Ord G and multicoloured join count statistics, local Moran's I and Getis/Ord G, saddlepoint approximations and exact tests for global and local Moran's I; and functions for estimating spatial simultaneous autoregressive (SAR) lag and error models, impact measures for lag models, weighted and unweighted SAR and CAR spatial regression models, semi-parametric and Moran eigenvector spatial filtering, GM SAR error models, and generalized spatial two stage least squares models.