Typical examples of the misfit of the secular variation models to the Southern African geomagnetic data for D, H, Z and F can be seen in Figs. 7, 8, 9 and 10, respectively.
From this perspective, keeping the maximum degree of IGRF predictive secular variation models to its present value would definitely avoid having to adjust this degree to the quality of the available data every time a new IGRF model is to be produced.
AIC indicates that GTR+I+Γ represents the optimal model in respect to the dataset (GTR = general time reversible, I = invariable sites, Γ = among-site rate variation modeled to fit a discrete gamma distribution).
This suggests the human variation model, according to which many of the challenges faced by disabled people do not result from their deliberate exclusion, but from a mismatch between their characteristics and the physical and social environment.
Since the synthetic Swarm vector measurements were generated using a secular variation model up to SH degree 20 (Olsen et al., 2013), the secular variation is only partly corrected for.
The authors in [18] propose a bivariate total variation regularization model to calibrate the volatility (sigma=sigma(S,t)), the existence and convergence for the regularized approach are discussed and some numerical experiments are presented.
Geometric variation model is introduced to infer key parts and key features, helping forming tolerance specification while assuring rationality and sufficiency of structure decomposition.
Conceptually, this rate variation model is equivalent to that under the UPM (Snir et al. 2012).
The total variation model has been considered to be one of the most successful and representative denoising models that can preserve edges well.
We can see that for SH degree 8 and below our EIGRF secular variation model is very similar to that of IGRF-10.
