gmdm: Generalized Minimum Distance Matrix

Description

Computing Generalized Minimum Distance Matrix

Usage

gmdm(data,labels,pseudocount=0,sliding=TRUE,resolution=1)
## S3 method for class `gmdm'
"print"(x, ...)
## convert a `gmdm' object into a `dist' object
gmdm2dist(m, diag=FALSE, upper=FALSE)
## compute GMDM and convert into a `dist' object
gmdm_dist(data, diag=FALSE, upper=FALSE, ...)

Arguments

data

a list of numeric vectors, a numeric matrix or data.frame

a gmdm object.

labels

a character vector of the same length of x, giving the names of the numeric vectors.

pseudocount

a numeric value to be allocated for each position to reduce bias; by default pseudocount = 0.

sliding

logical, indicating whether sliding is allowed or not for an optimal solution; by default sliding = TRUE.

resolution

relative resolution, numeric (>=1), changing the size of the bin by multiplying the value. A larger value (lower resolution) is more computational efficiet but missing details.

diag

logical value indicating whether the diagonal of the distance matrix should be printed by print.dist.

upper

logical value indicating whether the upper triangle of the distance matrix should be printed by print.dist.

...

arguments to be passed to method

Value

gmdm returns an object of class gmdm, a list with componentslabels: a string vector, giving the names of distributionsdata.ori: a list of numeric vectors, giving the original inputdata: a list of numeric vectors, giving the normalized version of the original inputdm: a numeric numeric, the pairwise distance matrix of GM-Distancesgap.pair: a numeric matrix, giving the gap pair of each alignment per row: i.e. relative shifts between distributions of the optimal hitsliding: logical, indicating whether sliding is performedpseudocount: a numeric value that is allocated at each position in addition to original values

Details