groupMetricsML: Calculate maximum likelihood based measures of dispersion of...
In AndrewLJackson/SIBER: Stable Isotope Bayesian Ellipses in R
View source: R/groupMetricsML.R
groupMetricsML R Documentation
Calculate maximum likelihood based measures of dispersion of bivariate data
Description
This function loops over each group within each community and calculates the
convex hull total area, Standard Ellipse Area (SEA) and its corresponding
small sample size corrected version SEAc based on the maximum likelihood
estimates of the means and covariance matrices of each group.
Usage
groupMetricsML(siber)
Arguments
siber
a siber object as created by createSiberObject.
Value
A 3 x m matrix of the 6 Layman metrics of dX_range, dY_range, TA,
CD, MNND and SDNND in rows, where each column is a different group nested
within a community.
Examples
data(demo.siber.data)
my.siber.data <- createSiberObject(demo.siber.data)
groupMetricsML(my.siber.data)
AndrewLJackson/SIBER documentation built on June 7, 2024, 3:21 a.m.
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View source: R/groupMetricsML.R
| groupMetricsML | R Documentation |
Calculate maximum likelihood based measures of dispersion of bivariate data
Description
This function loops over each group within each community and calculates the convex hull total area, Standard Ellipse Area (SEA) and its corresponding small sample size corrected version SEAc based on the maximum likelihood estimates of the means and covariance matrices of each group.
Usage
groupMetricsML(siber)
Arguments
siber |
a siber object as created by createSiberObject. |
Value
A 3 x m matrix of the 6 Layman metrics of dX_range, dY_range, TA, CD, MNND and SDNND in rows, where each column is a different group nested within a community.
Examples
data(demo.siber.data)
my.siber.data <- createSiberObject(demo.siber.data)
groupMetricsML(my.siber.data)
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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