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'.
| Version: | 0.2.5 |
| Depends: | R (≥ 3.5) |
| Imports: | Rcpp (≥ 0.12.16), keras (≥ 2.2.4) |
| LinkingTo: | Rcpp |
| Published: | 2020-05-12 |
| Author: | Xueying Tang [aut, cre], Susu Zhang [aut], Zhi Wang [aut], Jingchen Liu [aut], Zhiliang Ying [aut] |
| Maintainer: | Xueying Tang <xueyingtang1989 at gmail.com> |
| BugReports: | https://github.com/xytangtang/ProcData/issues |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| SystemRequirements: | Python (>= 2.7) |
| Materials: | README |
| CRAN checks: | ProcData results |
| Reference manual: | ProcData.pdf |
| Package source: | ProcData_0.2.5.tar.gz |
| Windows binaries: | r-devel: ProcData_0.2.5.zip, r-release: ProcData_0.2.5.zip, r-oldrel: ProcData_0.2.5.zip |
| macOS binaries: | r-release: ProcData_0.2.5.tgz, r-oldrel: ProcData_0.2.5.tgz |
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