solvecov: Invert of covariance matrices
In mrds: Mark-Recapture Distance Sampling
solvecov R Documentation
Invert of covariance matrices
Description
Tries to invert a matrix by solve. If this fails because of
singularity, an eigenvector decomposition is computed, and eigenvalues below
1/cmax are replaced by 1/cmax, i.e., cmax will be the
corresponding eigenvalue of the inverted matrix.
Usage
solvecov(m, cmax = 1e+10)
Arguments
m
a numeric symmetric matrix.
cmax
a positive value, see above.
Value
A list with the following components: inv the inverted
matrix, coll TRUE if solve failed because of
singularity.
Source
solvecov code was taken from package fpc: Christian Hennig
Author(s)
Christian Hennig
See Also
solve, eigen
mrds documentation built on May 29, 2024, 3:56 a.m.
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| solvecov | R Documentation |
Invert of covariance matrices
Description
Tries to invert a matrix by solve. If this fails because of
singularity, an eigenvector decomposition is computed, and eigenvalues below
1/cmax are replaced by 1/cmax, i.e., cmax will be the
corresponding eigenvalue of the inverted matrix.
Usage
solvecov(m, cmax = 1e+10)
Arguments
m |
a numeric symmetric matrix. |
cmax |
a positive value, see above. |
Value
A list with the following components: inv the inverted
matrix, coll TRUE if solve failed because of
singularity.
Source
solvecov code was taken from package fpc: Christian Hennig
Author(s)
Christian Hennig
See Also
solve, eigen
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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