DirichletLaplacePrior.coefficient_mean#
- DirichletLaplacePrior.coefficient_mean(context)[source]#
Zero everywhere: sparsity’s claim is that coefficients are zero.
There is no persistence hyperparameter here on purpose. Centering a selection prior away from zero would change what an exclusion means, so a caller who wants random-walk centering should difference the data or use the Minnesota family instead.