MAXLEN_est: Estimate MAXLEN

In SONO: Scores of Nominal Outlyingness (SONO)

Estimate MAXLEN

Description

Function estimating the value of MAXLEN (stopping criterion) prior to running the SONO algorithm. The estimation is done using the ideas described in \insertCitecosta_novel_2025;textualSONO, using simultaneous confidence intervals for Multinomial proportions, as done by \insertCitesison_simultaneous_1995;textualSONO.

Usage

MAXLEN_est(data, probs, alpha = 0.01, frequent = FALSE)

Arguments

data	Dataset; needs to be of class data.frame and consist of factor variables only.
probs	List of probability vectors for each variable. Each element of the list must include as many probabilities as the number of levels associated with it in the dataset.
alpha	Significance level for the simultaneous Multinomial confidence intervals constructed, determining what the frequency thresholds should be for itemsets of different length, used for outlier detection for discrete features. Must be a positive real, at most equal to 0.50. A greater value leads to a much more conservative algorithm. Default value is 0.01.
frequent	Logical determining whether highly frequent or highly infrequent itemsets are considered as outliers. Defaults to FALSE, treating highly infrequent itemsets as outlying.

Value

Estimated MAXLEN value.

References

\insertRef

costa_novel_2025SONO

\insertRef

sison_simultaneous_1995SONO

Examples

dt <- as.data.frame(sample(c(1:2), 100, replace = TRUE, prob = c(0.5, 0.5)))
dt <- cbind(dt, sample(c(1:3), 100, replace = TRUE, prob = c(0.5, 0.3, 0.2)))
dt[, 1] <- as.factor(dt[, 1])
dt[, 2] <- as.factor(dt[, 2])
colnames(dt) <- c('V1', 'V2')
MAXLEN_est(data = dt, probs = list(c(0.5, 0.5), c(1/3, 1/3, 1/3)), alpha = 0.01, frequent = FALSE)

SONO documentation built on April 12, 2025, 1:13 a.m.