Fixing logisticCoefs double dot bug

[kgoldfeld]

No description provided.

[github-actions]

This is how benchmark results would change (along with a 95% confidence interval in relative change) if b11e226 is merged into main:

• ✔️define_data: 17.7ms -> 17.7ms [-0.98%, +1.87%]
• ✔️dist_beta: 210ms -> 212ms [-0.19%, +2.95%]
• ✔️dist_binary: 8.66ms -> 8.58ms [-3.51%, +1.79%]
• ✔️dist_binomial: 13.3ms -> 13ms [-6.46%, +2.33%]
• ✔️dist_categorical: 62ms -> 60ms [-6.49%, +0.12%]
• ✔️dist_exponential: 8.76ms -> 8.84ms [-1.27%, +3.12%]
• ✔️dist_gamma: 16.3ms -> 16.2ms [-1.14%, +0.36%]
• ✔️dist_mixture: 224ms -> 226ms [-1.4%, +2.46%]
• ✔️dist_normal: 10.5ms -> 10.5ms [-0.76%, +1.05%]
• ✔️gen_all_dists: 49ms -> 48.9ms [-1.55%, +1.11%]
  Further explanation regarding interpretation and methodology can be found in the documentation.

[kgoldfeld]

@assignUser I fixed it with a few lines of code. Take a look and let me know if you think I can go ahead and merge it.

[assignUser]

Looks good! Adding a test for this might be a good idea though, to catch any regressions should there be changes (either to the double dot notation or how R handles envs or something :) ).

[github-actions]

This is how benchmark results would change (along with a 95% confidence interval in relative change) if 0fa7a0e is merged into main:

• ✔️define_data: 18.3ms -> 18.5ms [-2.91%, +5.31%]
• ✔️dist_beta: 216ms -> 218ms [-2.85%, +3.98%]
• ✔️dist_binary: 9.18ms -> 9.58ms [-9.19%, +17.85%]
• ✔️dist_binomial: 13.6ms -> 14ms [-3.99%, +11.14%]
• ✔️dist_categorical: 63.1ms -> 61.5ms [-5.13%, +0.02%]
• 🚀dist_exponential: 9.65ms -> 9.14ms [-9.51%, -1.05%]
• ✔️dist_gamma: 17ms -> 17.3ms [-1%, +4.2%]
• ✔️dist_mixture: 232ms -> 228ms [-3.74%, +0.46%]
• ✔️dist_normal: 11.5ms -> 11.7ms [-8.49%, +12.98%]
• ✔️gen_all_dists: 52.7ms -> 51.7ms [-4.65%, +0.84%]
  Further explanation regarding interpretation and methodology can be found in the documentation.

[kgoldfeld]

I've added a test and will merge now.