metric.ldata: Distance Matrix Computation for ldata and mfdata class object

In fda.usc: Functional Data Analysis and Utilities for Statistical Computing

Distance Matrix Computation for ldata and mfdata class object

Description

This function computes the distances between the list elements

Usage

metric.ldata(
  ldata1,
  ldata2 = NULL,
  include = "all",
  exclude = "none",
  metric,
  par.metric = NULL,
  w,
  method = "none"
)

Arguments

ldata1	List with of fdata objects and a data.frame object calle 'df'.
ldata2	List with of fdata objects and a data.frame object calle 'df'.
include	vector with the name of variables to use
exclude	vector with the name of variables to not use
metric	Type of metric to combine, if 'none', the function no combine and return a list o distances for each variable included
par.metric	List of metric parameters for each variable included
w,	weights to combine the metric (if metric is not 'none')
method	The distance measure to be used. This must be one of "euclidean", "maximum", "manhattan", "canberra", "binary" or "minkowski".

Details

This function returns a distance matrix by using metric.lp function for fdata objects and metric.dist function for vector and matric objects.

Author(s)

Manuel Febrero-Bande, Manuel Oviedo de la Fuente [e-mail]

See Also

See also dist for multivariate date case and metric.lp for functional data case

Examples

## Not run: 
data(tecator)
names(tecator)[2] <- "df"
# Example 1 (list of distances)
ldist <- metric.ldata(tecator,method="none")
lapply(ldist,names)
# Example 2 (combined metric)
mdist <- metric.ldata(tecator,method="euclidean")
dim(mdist) 

## End(Not run)

fda.usc documentation built on Oct. 17, 2022, 9:06 a.m.