sparse_pca: Predict aggregate growth based on sparse PCA decomposition
In tweed1e/idiosyncratics:
Description
Usage
Arguments
Value
View source: R/pca_functions.R
Description
A function that predicts an annual aggregate growth rate
by using a PCA decomposition of individual growth rates,
using a sparse PCA based on glmnet.
Usage
1
sparse_pca(X, W, pca = prcomp(X))
Arguments
X
A matrix of data
W
A matrix of weights
pca
The PCA decomposition of X
Value
A tbl of predictions of aggregate growth by year,
using the number of common factors given by hatr
tweed1e/idiosyncratics documentation built on May 29, 2019, 10:51 a.m.
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Description Usage Arguments Value
View source: R/pca_functions.R
Description
A function that predicts an annual aggregate growth rate by using a PCA decomposition of individual growth rates, using a sparse PCA based on glmnet.
Usage
1 | sparse_pca(X, W, pca = prcomp(X))
|
Arguments
X |
A matrix of data |
W |
A matrix of weights |
pca |
The PCA decomposition of X |
Value
A tbl of predictions of aggregate growth by year, using the number of common factors given by hatr
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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