Changes in version 0.99.1                        

  - data.type is now a required argument with no default. A new value,
    "abundance", covers non-count, non-proportional abundance data such
    as CPM or TPM values.
  - read.depth must now be chosen explicitly for count data. For other
    data types, it defaults to FALSE. Moreover, read depths supplied as
    a metadata column are now log10-transformed and added to the model
    automatically.
  - print() now reports also the estimated values of the hyperparameters
    of the hierarchical Laplace prior. For this to work keep.pars of
    dipper() now defaults to c("beta", "tau", "nu").
  - verbose argument is added to dipper(). Setting verbose = FALSE
    silences all messages, including those from Stan.
  - threshold is now always interpreted on the scale of the supplied
    data. For instance, for data.type = "counts", threshold = 2 means
    that count values of 2 or below are interpreted as absence.
  - The vignette and the details section of ?dipper have been updated
    regarding the type of the input data, controlling for sequencing
    depth, and the choice between the symmetric and the asymmetric
    hierarchical prior.
  - Bugs in parsing model formula have been fixed.

                       Changes in version 0.99.0                        

  - Initial Bioconductor submission.
  - Provides an implementation of DiPPER (Differential Prevalence via
    Probabilistic Estimation in R), a Bayesian hierarchical modeling
    approach for differential prevalence analysis, especially in
    microbiome studies.
  - Supports both cross-sectional and longitudinal (repeated measures)
    designs, with covariate adjustment and automatic control for
    sequencing depth.
  - Posterior inference is performed with CmdStan, which must be
    installed separately before installing DiPPER.