# Processing Non-Gaussian Data Residuals in Geomagnetism

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## Abstract

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## Featured Application

**A possible application of the data processing method described below is to separate noise due to external effects from noise due to the limited accuracy of the sensor itself. Such a model may reveal the need for a calibration process and impose some statistical constraints on external effects.**

## Abstract

**2017**, 209, 1036–1047.

## 1. Introduction

## 2. Mixture Model

#### 2.1. The Unformal Interpretation

#### 2.2. Version of the General Formula

#### 2.3. Sequential Small Mixtures

## 3. Method: Real Data Analysis

- $S{T}_{1}$: Satellite A ${\sigma}_{1}=2.41$${s}_{1}=0.33$, Satellite B ${\sigma}_{1}=2.40$${s}_{1}=0.36$
- $S{T}_{0.75}$: Satellite A ${\sigma}_{0.75}=2.34$${s}_{0.75}=0.36$, Satellite B ${\sigma}_{0.75}=2.35$${s}_{0.75}=0.39$
- $S{T}_{0.5}$: Satellite A ${\sigma}_{0.5}=2.22$${s}_{0.5}=0.39$, Satellite B ${\sigma}_{0.5}=2.21$${s}_{0.5}=0.46$
- $S{T}_{0.25}$: Satellite A ${\sigma}_{0.25}=1.99$${s}_{0.25}=0.43$, Satellite B ${\sigma}_{0.25}=1.96$${s}_{0.25}=0.49$

## 4. Discussion

## 5. Conclusions

## Funding

## Data Availability Statement

## Conflicts of Interest

## References

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**Figure 1.**Standard deviations (in nT) computed every day for the mid-latitude residuals of the Swarm scalar data used to compute the VFM model of Vigneron et al. (2015). Blue large dots: data from the Swarm Alpha satellite and red dots: data from the Swarm Bravo satellite. Days are counted in Julian days, with 1 January 2000 taken as the reference.

**Figure 2.**Left: Histogram of the residuals (circles) of the Swarm Alpha scalar data used to compute the VFM model [7] together with histogram (triangles) of an identical number of simulated mixture of Gaussian distributions according to the parameters $s=0.41$, $\sigma =2.18$ recovered from the real data; right: the same plots but for the Swarm Bravo scalar data, parameters $s=0.47$ and $\sigma =2.10$.

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**MDPI and ACS Style**

Khokhlov, A.
Processing Non-Gaussian Data Residuals in Geomagnetism. *Appl. Sci.* **2022**, *12*, 2097.
https://doi.org/10.3390/app12042097

**AMA Style**

Khokhlov A.
Processing Non-Gaussian Data Residuals in Geomagnetism. *Applied Sciences*. 2022; 12(4):2097.
https://doi.org/10.3390/app12042097

**Chicago/Turabian Style**

Khokhlov, Andrey.
2022. "Processing Non-Gaussian Data Residuals in Geomagnetism" *Applied Sciences* 12, no. 4: 2097.
https://doi.org/10.3390/app12042097