Package: pdmod 1.0.1
pdmod: Proximal/Distal Modeling Framework for Pavlovian Conditioning Phenomena
Fits a model of Pavlovian conditioning phenomena, such as response extinction and spontaneous recovery, and partial reinforcement extinction effects. Competing proximal and distal reward predictions, computed using fast and slow learning rates, combine according to their uncertainties and the recency of information. The resulting mean prediction drives the response rate.
Authors:
pdmod_1.0.1.tar.gz
pdmod_1.0.1.zip(r-4.5)pdmod_1.0.1.zip(r-4.4)pdmod_1.0.1.zip(r-4.3)
pdmod_1.0.1.tgz(r-4.5-x86_64)pdmod_1.0.1.tgz(r-4.5-arm64)pdmod_1.0.1.tgz(r-4.4-x86_64)pdmod_1.0.1.tgz(r-4.4-arm64)pdmod_1.0.1.tgz(r-4.3-x86_64)pdmod_1.0.1.tgz(r-4.3-arm64)
pdmod_1.0.1.tar.gz(r-4.5-noble)pdmod_1.0.1.tar.gz(r-4.4-noble)
pdmod_1.0.1.tgz(r-4.4-emscripten)pdmod_1.0.1.tgz(r-4.3-emscripten)
pdmod.pdf |pdmod.html✨
pdmod/json (API)
| # Install 'pdmod' in R: |
| install.packages('pdmod', repos = c('https://cbracis.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 7 years agofrom:86acb2f615. Checks:8 OK, 4 NOTE. Indexed: yes.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 25 2025 |
| R-4.5-win-x86_64 | NOTE | Mar 25 2025 |
| R-4.5-mac-x86_64 | NOTE | Mar 25 2025 |
| R-4.5-mac-aarch64 | NOTE | Mar 25 2025 |
| R-4.5-linux-x86_64 | NOTE | Mar 25 2025 |
| R-4.4-win-x86_64 | OK | Mar 25 2025 |
| R-4.4-mac-x86_64 | OK | Mar 25 2025 |
| R-4.4-mac-aarch64 | OK | Mar 25 2025 |
| R-4.4-linux-x86_64 | OK | Mar 25 2025 |
| R-4.3-win-x86_64 | OK | Mar 25 2025 |
| R-4.3-mac-x86_64 | OK | Mar 25 2025 |
| R-4.3-mac-aarch64 | OK | Mar 25 2025 |
Exports:averageBySessioncalculateResponsecomputeModelfitModelisTimedVectormodelObjectiveFunctionTimedVectorTV_DAYTV_HOURTV_MINUTEverifyTimedVector
Dependencies:mco
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Proximal/Distal Modeling Framework | pdmod-package pdmod |
| Average by session | averageBySession |
| Calculate response from the estimate | calculateResponse |
| Calculates proximal/distal model | computeModel |
| Constants | Constants TV_DAY TV_HOUR TV_MINUTE |
| Fit model parameters | fitModel |
| Is TimedVector | isTimedVector |
| Objective function to fit model parameters | modelObjectiveFunction |
| Plot model | plot.pdmod |
| Create a TimedVector | TimedVector |
| Verify TimedVector | verifyTimedVector |
