## Say we have that the tau posterior distribution from EpiBayes_ns() has mean and
## variance 0.01, and 0.015, respectively. The corresponding beta parameters will be:
utils_newalphbet(0.01, 0.015)
## If we provide a mean of 1, gives meaningful results
utils_newalphbet(1, 1)
## If we provide a mean of 0, gives meaningful results
utils_newalphbet(0, 1)
## Not run:
# ## Returns an error message if shape parameters cannot be coerced to be positive
# utils_newalphbet(1, -1)
# ## End(Not run)
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