RegSeqScore: Calculation of the Regular Sequence Scores

In jgillam13/IRASD: What the Package Does (One Line, Title Case)

Description

Calculation of the Regular Sequence Scores

Usage

RegSeqScore(seqlist, allsqs, sqsindex, catvec, probabilities, k, beta, lam)

Arguments

seqlist	List of sequences separated by time window.
allsqs	Matrix containing all the possible SQS for the possible categories.
sqsindex	Index Matrix indicating which sequences have which SQS's.
catvec	Vector of the different categories found in the sequences.
probabilities	Estimated proportion of each category seen in the sequences.
k	Maximum length of sequence silhouette.
beta	Score parameter.
lam	Score parameter.

Value

Regular sequences score matrix.

Examples

df<-data.frame(Time=c("2020-01-01 00:10:09", "2020-01-01 01:12:34" , "2020-01-02 06:38:09",
"2020-01-02 07:21:51"),Cat=c('A','B','A','C'))
#For daily data:
seqlist<-SeqList(df,'%Y-%m-%d')
sqslist<-SQSList(seqlist,2)
allsqs<-AllSQS(c('A','B','C'),2)
sqsindex<-SQSIndex(allsqs,sqslist)
RegSeqScore(seqlist,allsqs,sqsindex,c('A','B','C'),c(0.5,0.25,0.25),2,1,0.5)

jgillam13/IRASD documentation built on Feb. 10, 2021, 9:38 a.m.