Generic function to perform spatial smoothing of spatial data
 by diffusion.

SmoothHeat

Functionality for exploratory data analysis and nonparametric analysis of
spatial data, mainly spatial point patterns,
in the 'spatstat' family of packages.
(Excludes analysis of spatial data on a linear network,
which is covered by the separate package 'spatstat.linnet'.)
Methods include quadrat counts, K-functions and their simulation envelopes, 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, and kernel estimates of covariate effects. Formal hypothesis tests of random pattern (chi-squared, Kolmogorov-Smirnov, Monte Carlo, Diggle-Cressie-Loosmore-Ford, Dao-Genton, two-stage Monte Carlo) and tests for covariate effects (Cox-Berman-Waller-Lawson, Kolmogorov-Smirnov, ANOVA) are also supported.

Adrian Baddeley

spatstat.explore

Exploratory Data Analysis for the 'spatstat' Family

Rolf Turner

Ege Rubak

Kasper Klitgaard Berthelsen

Warick Brown

Achmad Choiruddin

Ya-Mei Chang

Jean-Francois Coeurjolly

Lucia Cobo Sanchez

Ottmar Cronie

Tilman Davies

Julian Gilbey

Jonatan Gonzalez

Yongtao Guan

Ute Hahn

Martin Hazelton

Kassel Hingee

Abdollah Jalilian

Frederic Lavancier

Marie-Colette van Lieshout

Greg McSwiggan

Robin K Milne

Tuomas Rajala

Suman Rakshit

Dominic Schuhmacher

Rasmus Plenge Waagepetersen

Hangsheng Wang

Tingting Zhan

SmoothHeat function

Spatial Smoothing of Data by Diffusion — SmoothHeat

<dl>

 <dt>X</dt>
<dd>Some kind of spatial data</dd>

 <dt>...</dt>
<dd>Arguments passed to methods.</dd>

</dl>

Arguments

Adrian Baddeley <a href='mailto:Adrian.Baddeley@curtin.edu.au'>Adrian.Baddeley@curtin.edu.au</a>.

Author

Spatial Smoothing of Data by Diffusion

SmoothHeat: Spatial Smoothing of Data by Diffusion

Description

Usage

Arguments

Value

Details

See Also