Probit with Spatial Dependence, SAR, SEM and SARAR Models
c(person(given = "Davide",
family = "Martinetti",
role = c("aut", "cre"),
email = "davide.martinetti@inrae.fr",
comment = c(ORCID = "0000-0003-2047-1793")),
person(given = "Ghislain",
family = "Geniaux",
role = "aut"))
Fast estimation of binomial spatial probit regression models with spatial autocorrelation for big datasets.
numDeriv, RANN, Rcpp (>= 1.0.4.6), methods
Davide Martinetti [aut, cre] (<https://orcid.org/0000-0003-2047-1793>),
Ghislain Geniaux [aut]

c(
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")))
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
of functions in 'keras'.
Xueying Tang [aut, cre],
Susu Zhang [aut],
Zhi Wang [aut],
Jingchen Liu [aut],
Zhiliang Ying [aut]

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
are wrappers of functions in 'keras'.