log_sparse_prior_W: The *un-normalised* prior over W in SpStPCA. This is a...
In JimSkinner/spca: Structured PCA
Description
Usage
Arguments
Value
Description
The *un-normalised* prior over W in SpStPCA. This is a product of
the StPCA Gaussian prior and an iid Laplace prior.
p(W | \beta, b) = \prod^k_i=1 N(w_i | 0, K) *
\prod^d_i=1 \prod^k_j=1 Laplace(W_ij | 0, b)
Usage
1
log_sparse_prior_W(K, W, b)
Arguments
K
Prior covariance matrix
W
Loadings matrix
b
Variance on Laplace part of prior
Value
un-normalised log prior over W
JimSkinner/spca documentation built on May 7, 2019, 10:52 a.m.
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Description Usage Arguments Value
Description
The *un-normalised* prior over W in SpStPCA. This is a product of the StPCA Gaussian prior and an iid Laplace prior. p(W | \beta, b) = \prod^k_i=1 N(w_i | 0, K) * \prod^d_i=1 \prod^k_j=1 Laplace(W_ij | 0, b)
Usage
1 | log_sparse_prior_W(K, W, b)
|
Arguments
K |
Prior covariance matrix |
W |
Loadings matrix |
b |
Variance on Laplace part of prior |
Value
un-normalised log prior over W
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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