distance_matrix_PMIME: Pairwise distance matrix based on the partial mutual...

In AnomalyScore: Anomaly Scoring for Multivariate Time Series

Pairwise distance matrix based on the partial mutual information of mixed embedings (PMIME) method

Description

Pairwise distance matrix based on the partial mutual information of mixed embedings (PMIME) method

Usage

distance_matrix_PMIME(unit, Lmax, Tl, nnei, A)

Arguments

unit	A matrix representing a multivariate time series where each column is a univariate time series.
Lmax	: the maximum delay to search for X and Y components for the mixed embedding vector ,default is 5.
Tl	: Tl steps ahead that the mixed embedding vector has to explain. Note that if Tl>1 the future vector is of length Tl and contains the samples at times t+1,..,t+Tl ,dafault is 1.
nnei	: number of nearest neighbors for density estimation ,default is 5
A	: the threshold for the ratio of CMI over MI of the lagged variables for the termination criterion.

Value

a matrix with pairwise distances

See Also

Kugiumtzis, D. "Direct-Coupling Information Measure from Nonuniform Embedding." Physical Review E 87, no. 6 (June 25, 2013): 062918. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.1103/PhysRevE.87.062918")}

Examples

X=matrix( rnorm(300), ncol=3  )
Lmax=2
Tl=1
nnei=5
A=.95
distance_matrix_PMIME(unit=X, Lmax, Tl, nnei, A )

AnomalyScore documentation built on April 4, 2025, 3:13 a.m.