Computes the euclidean distance between rows of a matrix X
and rows of another matrix Y.  Previously, this could be done
by binding the two matrices together and calling 'dist', but
this creates unnecessary computation by computing the distances
between a row of X and another row of X, and likewise for Y.
pdist strictly computes distances across the two matrices, not
within the same matrix, making computations significantly
faster for certain use cases.

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.

Proximal/distal modeling framework for Pavlovian conditioning
phenomena
This package provides 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.

Panel Dynamic OLS Estimation of Cointegrating Vectors
person("Raad", "Khraishi", email = "raadkhraishi+pdolsms@gmail.com", role = c("aut", "cre"))
Estimates panel data cointegrating relationships following the estimator of Mark and Sul (2003), <DOI:10.1111/j.1468-0084.2003.00066.x>.

A general framework for creating partial dependence plots from
various types machine learning models in R.
e1071, kernlab, nnet, party, partykit, randomForest, rpart,
testthat, xgboost
grDevices, lattice, magrittr, mgcv, plyr, stats, viridis

A general framework for constructing partial dependence plots from
various types of machine learning models in R.
C50, Cubist, e1071, kernlab, nnet, party, partykit,
randomForest, rpart, testthat, xgboost