Additional methods to potentially add

[gottacatchenall]

A list of potential sampling algorithms to add in future versions:

• Multidimensional GRTS: Re this paper. Basically: Generic coordinate + auxiliary variables in $\mathbb{R}^n \to \text{PCA} \to \mathbb{R}^2 \to \text{GRTS}$
• Dynamic Assignment Sampling: from this paper (note add methods used in Norman & Poisot (2025) #75)
• Fractal Triads: Simpson et al 2021 Proposed to measure phenomena across scales using a set of nested triangles
• Spatial Simulated Annealing van Groenigen 1998, and computational improvement by (Chen et al 2013). Optimizes spatial locations such that they minimize covariance among a set of spatial covariates (e.g. environmental raster data).
• Active Learning Query Strategies: from section three of this review. Note these typically require a model that you can take a gradient of