Establish prior hyperparameters for BAM estimation

Produces a bampriors object that can be passed to bam_estimate function

bam_priors(
  bamdata,
  variant = c("manning_amhg", "manning", "amhg"),
  classification = c("expert", "unsupervised"),
  ...
)

Arguments

bamdata	An object of class bamdata, as returned by bam_data
variant	Which BAM variant to use. Options are "manning_amhg" (default), "manning", or "amhg".
classification	Which classification framework to use. Options are 'expert' (default), or 'unsupervised'.
...	Optional manually set parameters. Unquoted expressions are allowed, e.g. logQ_sd = cv2sigma(0.8). Additionally, any variables present in bamdata may be referenced, e.g. lowerbound_logQ = log(mean(Wobs)) + log(5)