cov_pool: Computes the pooled maximum likelihood estimator (MLE) for...
In ramhiser/sparsediscrim: Sparse and Regularized Discriminant Analysis
Description
Usage
Arguments
Value
Examples
Description
For the matrix x, we compute the MLE for the population covariance
matrix under the assumption that the data are sampled from K
multivariate normal populations having equal covariance matrices.
Usage
1
cov_pool(x, y)
Arguments
x
data matrix with n observations and p feature vectors
y
class labels for observations (rows) in x
Value
pooled sample covariance matrix of size p \times p
Examples
1
ramhiser/sparsediscrim documentation built on May 26, 2019, 10:14 p.m.
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Description Usage Arguments Value Examples
Description
For the matrix x, we compute the MLE for the population covariance
matrix under the assumption that the data are sampled from K
multivariate normal populations having equal covariance matrices.
Usage
1 | cov_pool(x, y)
|
Arguments
x |
data matrix with |
y |
class labels for observations (rows) in |
Value
pooled sample covariance matrix of size p \times p
Examples
1 |
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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