cov_mle: Computes the maximum likelihood estimator for the sample...
In sparsediscrim: Sparse and Regularized Discriminant Analysis

Description Usage Arguments Details Value

For a sample matrix, x, we compute the sample covariance matrix of the data as the maximum likelihood estimator (MLE) of the population covariance matrix.

1	cov_mle(x, diag = FALSE)

`x`	data matrix with `n` observations and `p` feature vectors
`diag`	logical value. If TRUE, assumes the population covariance matrix is diagonal. By default, we assume that `diag` is `FALSE`.

If the diag option is set to TRUE, then we assume the population covariance matrix is diagonal, and the MLE is computed under this assumption. In this case, we return a vector of length p instead.

sample covariance matrix of size p \times p. If diag is TRUE, then a vector of length p is returned instead.

sparsediscrim documentation built on July 1, 2021, 9:07 a.m.