simplenet

A simple, artificially created, example of a linear network.

datasets

spatial

A package for analysing spatial data, mainly Spatial Point
        Patterns, including multitype/marked points and spatial
        covariates, in any two-dimensional spatial region. Also
        supports three-dimensional point patterns, and space-time point
        patterns in any number of dimensions. Contains over 1000
        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, pixel images and
        tessellations. Exploratory methods include K-functions, nearest
        neighbour distance and empty space statistics, Fry plots, pair
        correlation function, kernel smoothed intensity, relative risk
        estimation with cross-validated bandwidth selection, mark
        correlation functions, segregation indices, mark dependence
        diagnostics etc. Point process models can be fitted to point
        pattern data using functions ppm, kppm, slrm similar to glm.
        Models may include dependence on covariates, interpoint
        interaction, cluster formation 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).

simplenet: Simple Example of Linear Network

Description

Usage

Arguments

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