Man pages for ProcData
Process Data Analysis
| action_seqs_summary | Summarize action sequences |
| aseq2feature_seq2seq | Feature Extraction by action sequence autoencoder |
| atseq2feature_seq2seq | Feature Extraction by action and time sequence autoencoder |
| calculate_dist_cpp | Calculate "oss_action" dissimilarity matrix through Rcpp |
| cc_data | Data of item CP025Q01 (climate control item 1) in PISA 2012 |
| chooseK_mds | Choose the number of multidimensional scaling features |
| chooseK_seq2seq | Choose the number of autoencoder features |
| combine_actions | Combine consecutive actions into a single action |
| count_actions | Count action appearances |
| predict.seqm | Predict method for sequence models |
| print.proc | Print method for class '"proc"' |
| print.summary.proc | Print method for class '"summary.proc"' |
| proc | Class '"proc"' constructor |
| ProcData-package | ProcData: A package for process data analysis |
| read.seqs | Reading response processes from csv files |
| remove_action | Remove actions from response processes |
| remove_repeat | Remove repeated actions |
| replace_action | Replace actions in response processes |
| seq2feature_mds | Feature extraction via multidimensional scaling |
| seq2feature_mds_large | Feature Extraction by MDS for Large Dataset |
| seq2feature_mds_stochastic | Feature extraction by stochastic mds |
| seq2feature_ngram | ngram feature extraction |
| seq2feature_seq2seq | Feature Extraction by autoencoder |
| seq_gen | Action sequence generator |
| seq_gen2 | Markov action sequence generator |
| seq_gen3 | RNN action sequence generator |
| seqm | Fitting sequence models |
| sub_seqs | Subset response processes |
| summary.proc | Summary method for class '"proc"' |
| time_seqs_summary | Summarize timestamp sequences |
| tseq2feature_seq2seq | Feature Extraction by time sequence autoencoder |
| tseq2interval | Transform a timestamp sequence into a inter-arrival time... |
| write.seqs | Write process data to csv files |
