procrustes.syncsa: Procrustes and Partial Procrustes correlations.
In vanderleidebastiani/SYNCSA: Analysis of Functional and Phylogenetic Patterns in Metacommunities
Description
Usage
Arguments
Details
Value
Author(s)
References
See Also
Description
Function to obtain the Procrustes correlation between two matrices and
partial Procrustes correlation between three matrices.
Usage
1
2
3
procrustes.syncsa(x, y)
procrustes.partial.syncsa(x, y, z)
Arguments
x, y
Matrix that will be correlated.
z
Matrix whose effect will be removed from the correlation between x
and y.
Details
The function procrustes.syncsa is a small change in the function
procrustes. The function uses a correlation-like statistic
derived from the symmetric Procrustes sum of squares. Partial Procrustes
correlations is obtained by Procrustes correlation of residuals between
each variable in z being used as linear predictor of all variables in x and y.
For more details, see syncsa.
Value
Procrustes correlation between matrices.
Author(s)
Vanderlei Julio Debastiani <vanderleidebastiani@yahoo.com.br>
References
Peres-Neto, P.R. and Jackson, D.A. (2001). How well do
multivariate data sets match? The advantages of a Procrustean
superimposition approach over the Mantel test. Oecologia 129: 169-178.
See Also
vanderleidebastiani/SYNCSA documentation built on Sept. 4, 2020, 10:57 p.m.
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Description Usage Arguments Details Value Author(s) References See Also
Description
Function to obtain the Procrustes correlation between two matrices and partial Procrustes correlation between three matrices.
Usage
1 2 3 | procrustes.syncsa(x, y)
procrustes.partial.syncsa(x, y, z)
|
Arguments
x, y |
Matrix that will be correlated. |
z |
Matrix whose effect will be removed from the correlation between x and y. |
Details
The function procrustes.syncsa is a small change in the function
procrustes. The function uses a correlation-like statistic
derived from the symmetric Procrustes sum of squares. Partial Procrustes
correlations is obtained by Procrustes correlation of residuals between
each variable in z being used as linear predictor of all variables in x and y.
For more details, see syncsa.
Value
Procrustes correlation between matrices.
Author(s)
Vanderlei Julio Debastiani <vanderleidebastiani@yahoo.com.br>
References
Peres-Neto, P.R. and Jackson, D.A. (2001). How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test. Oecologia 129: 169-178.
See Also
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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