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bkmr 0.2.2

Bug fixes

• Corrected code that produced warning length > 1 in coercion to logical

• Update functions that use deprecated functions from dplyr package

Minor changes

• 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

bkmr 0.2.1

Bug fixes

• 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()

bkmr 0.2.0

Major changes

• 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())

Bug fixes

• Fixed PredictorResponseBivarLevels() when argument both_pairs = TRUE (#4)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.