momentum_dtw {distantia}R Documentation

Dynamic Time Warping Variable Importance Analysis of Multivariate Time Series Lists

Description

Minimalistic but slightly faster version of momentum() to compute dynamic time warping importance analysis with the "robust" setup in multivariate time series lists.

Usage

momentum_dtw(tsl = NULL, distance = "euclidean")

Arguments

tsl

(required, time series list) list of zoo time series. Default: NULL

distance

(optional, character vector) name or abbreviation of the distance method. Valid values are in the columns "names" and "abbreviation" of the dataset distances. Default: "euclidean".

Value

data frame:

See Also

Other momentum: momentum(), momentum_ls()

Examples


tsl <- tsl_initialize(
  x = distantia::albatross,
  name_column = "name",
  time_column = "time"
) |>
  tsl_transform(
    f = f_scale_global
  )

df <- momentum_dtw(
  tsl = tsl,
  distance = "euclidean"
  )

#focus on important columns
df[, c(
  "x",
  "y",
  "variable",
  "importance",
  "effect"
  )]


[Package distantia version 2.0.0 Index]