Function bayes_estimate::estimators::sir::roughen_minmax

pub fn roughen_minmax<N: RealField, D: Dim>(
    s: &mut Samples<N, D>, 
    k: f32, 
    rng: &mut dyn RngCore
) where
    DefaultAllocator: Allocator<N, D, D> + Allocator<N, D>, 

Roughen sample state using min max roughening of the samples.

Uses algorithm from Ref[1] which applies then the states have a singe locality but the distribution is unknown. max-min in each state dimension in the samples determines the amount of normally distributed noise added to that dimension for each sample.

‘k’ is scaling factor for normally distributed noise

Numerics: If the are very few unique samples the roughening will colapse as it is not representative of the true state distribution.