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cjbart 0.3.2

• Update documentation: correct details line for cjbart().
• Add compatibility so passing seed argument on Windows returns warning rather than error
• Add unit tests for OS compatibility

cjbart 0.3.1

• Fix documentation: to plot the variable importance grid, the x argument takes the result of calling het_vimp() and not IMCE() as previously documented (in v0.3.0)

• Update package dependencies

cjbart 0.3.0

• Rename arguments in het_vimp() from model to imces and outcomes to levels for consistency across functions
• Change het_vimp() so it returns a list, including the results and an attribute-level look-up table
• Added ability to run het_vimp() calculation in parallel
• Fixed bug when predicting continuous conjoint outcomes
• Add new pIMCE() function to calculate population individual-level marginal component effects
• Add new AMCE() function that includes Bayesian uncertainty estimate
• Add check for unique levels across attributes. If not, the attribute-level values are modified to ensure uniqueness
• Add functionality to improve quality of outputs
• Update the vignette to reflect new functionality
• Add ability to drop attributes from IMCE analysis
• Remove dependencies not needed

cjbart 0.2.2

• Re-release after dependencies back on CRAN

cjbart 0.2.1

• Minor internal changes to keep pace with R development
• Minor changes to vignette wording

cjbart 0.2.0

• Addresses unbalanced chunk delimiters in package vignette
• Adds new functionality for analyzing heterogeneity after IMCE prediction using random forest variable importance measures

cjbart 0.1.0

• First release including all core functionality
• Includes wrapper of BART estimation, IMCE prediction, and generics

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.