person("Xueying", "Tang", email = "xueyingtang1989@gmail.com", role = c("aut", "cre")),
person("Susu", "Zhang", email = "susu.zhang1992@gmail.com", role = c("aut")),
person("Zhi", "Wang", email = "zhiwpku@gmail.com", role=c("aut")),
person("Jingchen", "Liu", email = "jcliu@stat.columbia.edu", role=c("aut")),
person("Zhiliang", "Ying", email = "zying@stat.columbia.edu", role=c("aut")))
Description: General tools for exploratory process data analysis. Process data refers to the data describing
participants' problem solving processes in computer-based assessments. It is often recorded in computer
log files. This package provides two action sequence generators and implements two automatic feature extraction methods that compress the information
stored in process data, which often has a nonstandard format, into standard numerical vectors. This package
also provides recurrent neural network based models that relate response processes with other binary or
scale variables of interest. The functions that involve training and evaluating neural networks are wrappers
Packaged: 2020-05-09 03:25:06 UTC; xueyingtang

Description: Provides tools for exploratory process data analysis. Process data refers to the data describing
participants' problem-solving processes in computer-based assessments. It is often recorded in computer
log files. This package provides functions to read, process, and write process data. It also implements
two feature extraction methods to compress the information stored in process data into standard
numerical vectors. This package also provides recurrent neural network based models that relate response processes
with other binary or scale variables of interest. The functions that involve training and evaluating neural networks
SystemRequirements: Python (>= 2.7), Keras (>= 2.0), TensorFlow (>=
Packaged: 2021-03-25 05:31:36 UTC; xueyingtang

Title: Informative Procrustean Matrix Correlation
Author: Eric Coissac, Christelle Gonindard-Melodelima
Description: Estimates corrected Procrustean correlation between matrices for removing overfitting effect. Coissac Eric and Gonindard-Melodelima Christelle (2019) <bioarXiv:10.1101/842070>.
Imports: MASS, permute, expm, Matrix, mvtnorm, stats, foreach, Rdpack
Suggests: knitr, rmarkdown, roxygen2, vegan, testthat, ade4, doParallel
Collate: 'internals.R' 'procmod_frame.R' 'multivariate.R' 'procmod.R'