denseQR: Generate dense matrices (via spectral decomposition)
In SCPME: Shrinking Characteristics of Precision Matrix Estimators
Description
Usage
Arguments
Value
Description
Generate p-dimensional matrices so that its inverse is dense. The matrix will be generated so its first 'num' eigen values are 1000 and the remaining are 1. The orthogonal basis is generated via QR decomposition of
Usage
1
Arguments
p
desired dimension
num
number of 'large' eigen values. Note num must be less than p
n
option to generate n observations from covariance matrix S
Value
Omega, S
SCPME documentation built on May 2, 2019, 3:42 a.m.
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Description Usage Arguments Value
Description
Generate p-dimensional matrices so that its inverse is dense. The matrix will be generated so its first 'num' eigen values are 1000 and the remaining are 1. The orthogonal basis is generated via QR decomposition of
Usage
1 |
Arguments
p |
desired dimension |
num |
number of 'large' eigen values. Note num must be less than p |
n |
option to generate n observations from covariance matrix S |
Value
Omega, S
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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