# Process Data Analysis

## Documentation for package ‘ProcData’ version 0.2.5

- DESCRIPTION file.

## Help Pages

ProcData-package | ProcData: A package for 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 dissimilarity matrix
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"'
proc | Class '"proc"' constructor
ProcData | 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_seq2seq | Feature Extraction by autoencoder
seqm | Fitting sequence models
seq_gen | Action sequence generator
seq_gen2 | Markov action sequence generator
seq_gen3 | RNN action sequence generator
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 sequence
write.seqs | Write process data to csv files