Generation of Spatial Data with Spatially Varying Model
Parameter
A spatial population can be generated based on spatially varying regression model under the assumption that observations are collected from a uniform two-dimensional grid consist of (m * m) lattice points with unit distance between any two neighbouring points. For method details see Chao, Liu., Chuanhua, Wei. and Yunan, Su. (2018).<DOI:10.1080/10485252.2018.1499907>.  This spatially generated data can be used to test different issues related to the statistical analysis of spatial data.
This generated spatial data can be utilized in geographically weighted regression analysis for studying the spatially varying relationships among the variables.

Felipe Osorio <felipe.osorios@usm.cl> and Ronny Vallejos
<ronny.vallejos@usm.cl>, with contributions of Francisco Cuevas
and Diego Mancilla.
This package provides tools to assess the association between two spatial processes.
Currently, three methodologies are implemented: An adapted t-test to perform hypothesis
testing about the independence between the processes, a suitable nonparametric correlation
coefficient, and the codispersion coefficient. SpatialPack gives methods to complement
methodologies that are available in geoR for one spatial process.

Felipe Osorio <felipe.osorios@usm.cl>, Ronny Vallejos
<ronny.vallejos@usm.cl>, and Francisco Cuevas
<francisco.cuevas@alumnos.usm.cl>
This package provides tools to assess the association
between two spatial processes.  Currently, three methodologies
are implemented: An adapted t test to perform hypothesis
testing about the independence between the processes, a
suitable nonparametric correlation coefficient, and the
codispersion coefficient. Spatools gives methods to complement
methodologies that are available in geoR for one spatial
process.

Tools for Assessment the Association Between Two Spatial
Processes
Tools to assess the association between two spatial processes. Currently,
several methodologies are implemented: A modified t-test to perform hypothesis testing
about the independence between the processes, a suitable nonparametric correlation
coefficient, the codispersion coefficient, and an F test for assessing the multiple
correlation between one spatial process and several others. Functions for image
processing and computing the spatial association between images are also provided.
SpatialPack gives methods to complement methodologies that are available in geoR
for one spatial process.
c(person("Felipe", "Osorio", role = c("aut", "cre"), email = "felipe.osorios@usm.cl"),
person("Ronny", "Vallejos", role = "aut", email = "ronny.vallejos@usm.cl"),
person("Francisco", "Cuevas", role = "ctb"),
person("Diego", "Mancilla", role = "ctb"))
Felipe Osorio [aut, cre],
Ronny Vallejos [aut],
Francisco Cuevas [ctb],
Diego Mancilla [ctb]