rstanarm v2.21.1

rstanarm 2.21.1

• Compatible with rstan v2.21.1
• Consistent with new book Regression and Other Stories

Backwards incompatible changes

• stan_jm() is not available for 32bit Windows

• Some improvements to prior distributions, as described in detail in the vignette
  Prior Distributions for rstanarm Models and book Regression and Other Stories.
  These changes shouldn't cause any existing code to error, but default priors have
  changed in some cases:

  • default prior on intercept is still Gaussian but the way the location and
    scale are determined has been updated (#432)
  • autoscale argument to functions like normal(), student_t(), etc.,
    now defaults to FALSE except when used by default priors (default
    priors still do autoscalinng). This makes it simpler to specify non-default
    priors. (#432)

Bug fixes

• Fixed error in kfold() for stan_gamm4() models that used random argument (#435)
• Fixed error in posterior_predict() and posterior_linpred() when using newdata with
  family = mgcv::betar (#406, #407)
• singular.ok now rules out singular design matrices in stan_lm() (#402)
• Fix a potential error when data is a data.table object (#434, @danschrage)

New functions

• New method posterior_epred() returns the posterior distribution of the
  conditional expectation, which is equivalent to (and may eventually entirely
  replace) setting argument transform=TRUE with posterior_linpred(). (#432)

• Added convenience functions logit() and invlogit() that are just wrappers
  for qlogis() and plogis(). These were previously provided by the arm
  package. (#432)