cov_d

<p>A random covariance matrix to simulate data errors
The main ideia is described in figure 3 on Wentzell, P. D.
"Other topics in soft-modeling: maximum likelihood-based soft-modeling
methods." (2009): 507-558.</p>

datasets

R implementation of Maximum Likelihood Principal Component Analysis
The main idea of this package is to have an alternative way of PCA for
subspace modeling that considers measurement errors.
More details can be found in Peter D. Wentzell (2009)
<doi:10.1016/B978-0-444-64165-6.03029-9>.

Renan Santos Barbosa

RMLPCA

Maximum Likelihood Principal Component Analysis

cov_d function

<p>A matrix with 20 rows and 20 columns</p>

cov_d: Covariance matrix for mlpca_d model

Description

Usage

Arguments

Format

References