MinimumVarianceAnalysis

The main purpose of minimum or maximum variance analysis (MVA) is to find an estimator for the direction normal $\hat{𝐧}$ to an approximately one-dimensional structure, by minimisation of

$$ σ^2=\frac{1}{M} ∑_{m=1}^M | (𝐁^{(m)}-⟨𝐁⟩) · \hat{𝐧}|^2. $$

See SPEDAS for more details. See SPEDAS validation for comparison with a Python implementation (pyspedas).

Installation

using Pkg
Pkg.add("MinimumVarianceAnalysis")

Reference

• Sonnerup, B. U. Ö., & Scheible, M. (1998). Minimum and maximum variance analysis. ISSI Scientific Reports Series, 1, 185–220.

Roadmap

• Minimum Variance Analysis on Mass Flux (MVAρv)
• Maximum Variance Analysis on Electric Field (MVAE)
• Application to 2-D Structures

Notes

• Anisotropic fluctuations have been shown to lead to larger errors in normal determinations.