R-multiverse topic

stantargets 0.1.2

• Add R-multiverse topic.

hashing

stantargets 0.1.1

Invalidating changes

• To align with ropensci/targets#1244 and ropensci/targets#1262, switch the hashing functions from digest::digest() to secretbase::siphash13().

Other changes

• Remove temporary files generated CmdStan.
• Add the new description arguments of tar_target() (`targets >= 1.5.1.9001).
• Append model file information to the target descriptions using tar_map() (tarchetypes >= 0.7.12.9001).

SBC

stantargets 0.1.0

• Add a new transform argument to the tar_stan_*_rep_draws() functions (except mle) to support simulation-based calibration (SBC) (#31, @mike-lawrence, @martinmodrak, @dmi3kno).

Resilient rep-specific seeds

stantargets 0.0.6

• Implement resilient rep-specific seeds that do not change if the batching structure changes.

Function signature update

stantargets 0.0.5

• Update the signatures of most user-side functions to accommodate changes from cmdstanr 0.2.0 to 0.5.0 (ropensci/targets#884, @stuvet).

from stantargets 0.0.4:

• Support the repository argument for targets >= 0.11.0.
• Append a new .dataset_id column to target outputs to aid in model comparisons across the same datasets.

Documentation update

stantargets 0.0.3

• Update docs to changes in cmdstanr, posterior, and targets.

Cite JOSS paper

0.0.2

Reference JOSS paper

First release

stantargets 0.0.1

• Skip tests if CmdStan is not installed (@sakrejda).
• Use custom generate_data() function in the docs, as opposed to tar_stan_example_data() directly (@sakrejda).
• Add the pedantic argument for compilation (@sakrejda).
• Reduce dependencies on some rlang functions like sym() (@sakrejda).
• Change trn() to if_any() (@mattwarkentin, @sakrejda, @tjmahr).
• Add @sakrejda and @mattwarkentin as reviewers in the DESCRIPTION.
• Talk about the R package and system dependencies of stantargets in the README (@mattwarkentin).
• Throw an error earlier if the Stan file does not exist (@sakrejda, @mattwarkentin)
• Use @format roxygen2 tag for data generation (@mattwarkentin).
• Use @family go cross-reference functions (@mattwarkentin).
• Elaborate on the roles and return values of specific targets generated by target factories (@mattwarkentin).
• Undergo rOpenSci peer review and transition to rOpenSci.
• Link to an example project.