rubin_copy: Very inefficient copy of Rubin and Thayer iteration mostly...
In dcgerard/vicar: Various Ideas for Confounder Adjustment in Regression
Description
Usage
Arguments
Author(s)
Description
Very inefficient copy of Rubin and Thayer iteration mostly meant for debugging.
Usage
1
rubin_copy(alpha_sigma, S, n, p, k)
Arguments
alpha_sigma
A vector. The first k * p elements are the
vectorization of alpha. The last elements are sig_diag.
S
A matrix. This is the sample covariance matrix of the
samples that don't have a missing block.
n
The sample size
p
The number of genes.
k
The rank of the mean.
Author(s)
David Gerard
dcgerard/vicar documentation built on July 7, 2021, 1:08 p.m.
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Description Usage Arguments Author(s)
Description
Very inefficient copy of Rubin and Thayer iteration mostly meant for debugging.
Usage
1 | rubin_copy(alpha_sigma, S, n, p, k)
|
Arguments
alpha_sigma |
A vector. The first k * p elements are the vectorization of alpha. The last elements are sig_diag. |
S |
A matrix. This is the sample covariance matrix of the samples that don't have a missing block. |
n |
The sample size |
p |
The number of genes. |
k |
The rank of the mean. |
Author(s)
David Gerard
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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