makeVariance: makeVariance: Create variances for the components in data...
In trbKnl/sparseWeightBasedPCA: Sparse weight based PCA
Description
Usage
Arguments
Value
Examples
Description
A function that creates realistic variances for J components. The variances of the first Q components are set by the user, the remaining J - Q variances
are decreasing on a reversed log scale.
Usage
1
makeVariance(varianceOfComps, J, error)
Arguments
J
The total number of components (the number of variables)
error
The total variance of J-Q components compared to the variance of the Q components
varianceOfcomp
The variances of the first Q components of interest
Value
A vector with J variances (eigenvalues) to simulate data from.
Examples
1
2
variances <- makeVariance(c(120, 100, 80), J = 50, error = 0.05)
plot(variances) #realistic eigenvalues of a data matrix X
trbKnl/sparseWeightBasedPCA documentation built on July 22, 2020, 10:29 p.m.
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Description Usage Arguments Value Examples
Description
A function that creates realistic variances for J components. The variances of the first Q components are set by the user, the remaining J - Q variances are decreasing on a reversed log scale.
Usage
1 | makeVariance(varianceOfComps, J, error)
|
Arguments
J |
The total number of components (the number of variables) |
error |
The total variance of J-Q components compared to the variance of the Q components |
varianceOfcomp |
The variances of the first Q components of interest |
Value
A vector with J variances (eigenvalues) to simulate data from.
Examples
1 2 | variances <- makeVariance(c(120, 100, 80), J = 50, error = 0.05)
plot(variances) #realistic eigenvalues of a data matrix 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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