d_score

d score measures the similarity of two square matrix with same dimension. d_score equals 0 if the estimator is a column permutation of true value.

Provides functions for blind source separation over multivariate spatial data, and useful statistics for evaluating performance of estimation on mixing matrix. 'BSSoverSpace' is based on an eigen analysis of a positive definite matrix defined in terms of multiple normalized spatial local covariance matrices, and thus can handle moderately high-dimensional random fields. This package is an implementation of the method described in Zhang, Hao and Yao (2022)<arXiv:2201.02023>.

Sixing Hao

BSSoverSpace

Blind Source Separation for Multivariate Spatial Data using
Eigen Analysis

d_score function

<dl><dt>estimator</dt>
<dd>A square matrix, usually an estimator of the <code>true_value</code> matrix.</dd>
<dt>true_value</dt>
<dd>A square matrix, which the estimator is compared to.</dd></dl>

Arguments

d score — d_score

<dl>

<dt>estimator</dt>
<dd>A square matrix, usually an estimator of the <code>true_value</code> matrix.</dd>


<dt>true_value</dt>
<dd>A square matrix, which the estimator is compared to.</dd>

</dl>

d_score: d score

Description

Usage

Value

Arguments

Examples