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.

Version:	1.0.1
Imports:	mco, stats
Suggests:	RUnit
Published:	2018-02-13
Author:	Chloe Bracis
Maintainer:	Chloe Bracis <cbracis at uw.edu>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	yes
CRAN checks:	pdmod results

Documentation:

Reference manual:	pdmod.pdf
Vignettes:	pdmod

Downloads:

Package source:	pdmod_1.0.1.tar.gz
Windows binaries:	r-devel: pdmod_1.0.1.zip, r-release: pdmod_1.0.1.zip, r-oldrel: pdmod_1.0.1.zip
macOS binaries:	r-release (arm64): pdmod_1.0.1.tgz, r-oldrel (arm64): pdmod_1.0.1.tgz, r-release (x86_64): pdmod_1.0.1.tgz, r-oldrel (x86_64): pdmod_1.0.1.tgz
Old sources:	pdmod archive

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