nearPPSD: nearest positive semi-definite projection of a matrix
In robustcov: Collection of Robust Covariance and (Sparse) Precision Matrix Estimators
Description
Usage
Arguments
Value
Description
This routine calculate the nearest positive semi0definite projection
Usage
1
nearPPSD(X, eigenTol = 1e-06, convTol = 1e-07, psdTol = 1e-08, maxit = 1000L)
Arguments
X
the matrix
eigenTol
tolerance in eigen system, used in finding nearest positive matrix
convTol
tolerance in cov, used in finding nearest positive matrix
psdTol
tolerance in psd, used in finding nearest positive matrix
maxit
max iterations in finding nearest positive matrix
Value
a matrix which is the nearest positive semi-definite matrix of input X
robustcov documentation built on Aug. 4, 2021, 5:07 p.m.
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Description Usage Arguments Value
Description
This routine calculate the nearest positive semi0definite projection
Usage
1 | nearPPSD(X, eigenTol = 1e-06, convTol = 1e-07, psdTol = 1e-08, maxit = 1000L)
|
Arguments
X |
the matrix |
eigenTol |
tolerance in eigen system, used in finding nearest positive matrix |
convTol |
tolerance in cov, used in finding nearest positive matrix |
psdTol |
tolerance in psd, used in finding nearest positive matrix |
maxit |
max iterations in finding nearest positive matrix |
Value
a matrix which is the nearest positive semi-definite matrix of input X
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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