BoundaryCalculation: Internal function for identifying boundaries from spatial...
In ArdernHB/GeoOrigins: Spatial exploration of trait boundaries and provenance
View source: R/Boundary_functions.R
BoundaryCalculation R Documentation
Internal function for identifying boundaries from spatial correlation scores.
Description
This is an internal function to support the BoundaryFinder functions.
This function takes the correlation values calculated across the spatial grid and identifies which grid points are at the boundary of of the provenancing region.
These results then allow for the construction of compiled trait boundaries from spatial provenancing exercises.
Usage
BoundaryCalculation(MapMatrix, PlotValCor)
Arguments
MapMatrix
a matrix of correlation values that correspond to grid reference locations
PlotValCor
numeric correlation value that is used to determine the most likely origin of the specimen. This value can be calculated by using the correct cross-validation method and identifying the correlation value that will correctly identify a desired percentage of specimens (e.g. 95%).
Value
This function returns a matrix of logical TRUE/FALSE values identifying the boundary of the desired correlation value.
Author(s)
Ardern Hulme-Beaman
ArdernHB/GeoOrigins documentation built on Nov. 19, 2022, 10:21 a.m.
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View source: R/Boundary_functions.R
| BoundaryCalculation | R Documentation |
Internal function for identifying boundaries from spatial correlation scores.
Description
This is an internal function to support the BoundaryFinder functions. This function takes the correlation values calculated across the spatial grid and identifies which grid points are at the boundary of of the provenancing region. These results then allow for the construction of compiled trait boundaries from spatial provenancing exercises.
Usage
BoundaryCalculation(MapMatrix, PlotValCor)
Arguments
MapMatrix |
a matrix of correlation values that correspond to grid reference locations |
PlotValCor |
numeric correlation value that is used to determine the most likely origin of the specimen. This value can be calculated by using the correct cross-validation method and identifying the correlation value that will correctly identify a desired percentage of specimens (e.g. 95%). |
Value
This function returns a matrix of logical TRUE/FALSE values identifying the boundary of the desired correlation value.
Author(s)
Ardern Hulme-Beaman
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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