make.positive.definite: Compute Nearest Positive Definite Matrix
In gforge/lqmm_gforge: Linear Quantile Mixed Models
Description
Usage
Arguments
Author(s)
Source
View source: R/auxiliary_positive.definite.R
Description
This function computes the nearest positive definite of a real symmetric
matrix. See help("make.positive.definite") from package
corpcor.
Usage
1
make.positive.definite(m, tol)
Arguments
m
a matrix (assumed to be real and symmetric)
tol
tolerance for singular values and for absolute eigenvalues - only those with values
larger than tol are considered non-zero (default: tol = max(dim(m))*max(D)*.Machine$double.eps)
Author(s)
Original version by Korbinian Strimmer
Source
Juliane Schaefer, Rainer Opgen-Rhein, Verena Zuber, A. Pedro Duarte
Silva and Korbinian Strimmer. (2011). corpcor: Efficient Estimation of
Covariance and (Partial) Correlation. R package version 1.6.0.
https://CRAN.R-project.org/package=corpcor
gforge/lqmm_gforge documentation built on Dec. 20, 2021, 10:42 a.m.
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Description Usage Arguments Author(s) Source
View source: R/auxiliary_positive.definite.R
Description
This function computes the nearest positive definite of a real symmetric
matrix. See help("make.positive.definite") from package
corpcor.
Usage
1 | make.positive.definite(m, tol)
|
Arguments
m |
a matrix (assumed to be real and symmetric) |
tol |
tolerance for singular values and for absolute eigenvalues - only those with values larger than tol are considered non-zero (default: tol = max(dim(m))*max(D)*.Machine$double.eps) |
Author(s)
Original version by Korbinian Strimmer
Source
Juliane Schaefer, Rainer Opgen-Rhein, Verena Zuber, A. Pedro Duarte Silva and Korbinian Strimmer. (2011). corpcor: Efficient Estimation of Covariance and (Partial) Correlation. R package version 1.6.0. https://CRAN.R-project.org/package=corpcor
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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