bkmr 0.2.2

Bug fixes

No longer export the following functions:
- CalcGroupPIPs, CalcWithinGroupPIPs, and CalcPIPs as these should typically be calculated using the function ExtractPIPs
- ComputePostmeanHnew.approx and ComputePostmeanHnew.exact as these should typically be calculated using the function ComputePostmeanHnew
- set_verbose_opts as this is only called internally
Expanded function documentation by adding example code

allowable values for starting parameter for r[m] parameters updated as follows
- no longer truncated to a single value (when varsel = FALSE and rmethod = "varying")
- can be equal to 0 (when varsel = TRUE)
Error no longer generated if starting values for h.hat are not positive
When checking class of an object, use inherits() instead of class()

Added ability to have binomial outcome family by implementing probit regression within kmbayes()
Removed computation of the subject-specific effects h[i] within kmbayes(), as this is not always desired, and greatly slows down model fitting
- This could still be done by setting the option est.h = TRUE in the kmbayes function
- posterior samples of h[i] can now be obtained via the post-processing SamplePred function; alternatively, posterior summaries (mean, variance) can be obtained via the post-processing ComputePostmeanHnew function
Added ability to use exact estimates of the posterior mean and variance by specifying the argument method = 'exact' within the post-processing functions (e.g., OverallRiskSummaries(), PredictorResponseUnivar())