bqs_rank: Ranking Clusters Quadratic Scores Estimated Via Boostrap

In qcluster: Clustering via Quadratic Scoring

Ranking Clusters Quadratic Scores Estimated Via Boostrap

Description

Ranks the scores of clusters methods estimated via boostrap

Usage

   bqs_rank(bqsol, rankby = "lq", boot_na_share = 0.25)
   

Arguments

bqsol	an object of class bqs obtained from bqs.
rankby	character string specifying how the scored solution are ranked. Possible values are {"lq", "mean", "1se"}. With ="lq" (default), the solutions are ranked by maximizing the estimated lower limit of the of the 1-alpha bootstrap confidence intervalfor the expected score. With ="mean", the solutions are ranked by maximizing the estimated expected score. With ="1se", the solutions are ranked by maximizing the estimated lower limit of the confidence interval for the expected score whose semi-length is equal to a standard error. The expected score's standard error is approximated using the boostrap distribution.
boot_na_share	a numeric value in (0,1). During the boostrapping a method's score is set to NA if the underlying comptutation runs into errors. Methods resulting in more than B * boot_na_share errors are excluded from the comparison

Value

An S3 object of class bqs. Output components are those of bqs. See Value in bqs.

References

Coraggio, Luca and Pietro Coretto (2023). Selecting the number of clusters, clustering models, and algorithms. A unifying approach based on the quadratic discriminant score. Journal of Multivariate Analysis, Vol. 196(105181), 1-20. doi: \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1016/j.jmva.2023.105181")}

See Also

bqs

Examples

# load data
data("banknote")
dat <- banknote[-1]

## set up methods
## see also help('mset_user')  and related functions 
KM   <- mset_kmeans(K = 3)
GMIX <- mset_gmix(K=3, erc=c(1,100)) 

# combine tuned methods
mlist <- mbind(KM, GMIX)

# perform bootstrap
# change B and ncores to a much larger value in real problems 
res <- bqs(dat, mlist, B = 3, rankby="lq", ncores=1)
res

   
# now change ranking criterion
res2 <- bqs_rank(res, rankby="mean")
res2

qcluster documentation built on April 3, 2025, 6:16 p.m.