momentum_ls {distantia} | R Documentation |
Lock-Step Variable Importance Analysis of Multivariate Time Series Lists
Description
Minimalistic but slightly faster version of momentum()
to compute lock-step importance analysis in multivariate time series lists.
Usage
momentum_ls(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:
-
x
: name of the time seriesx
. -
y
: name of the time seriesy
. -
psi
: psi score ofx
andy
. -
variable
: name of the individual variable. -
importance
: importance score of the variable. -
effect
: interpretation of the "importance" column, with the values "increases similarity" and "decreases similarity".
See Also
Other momentum:
momentum()
,
momentum_dtw()
Examples
tsl <- tsl_initialize(
x = distantia::albatross,
name_column = "name",
time_column = "time"
) |>
tsl_transform(
f = f_scale_global
)
df <- momentum_ls(
tsl = tsl,
distance = "euclidean"
)
#focus on important columns
df[, c(
"x",
"y",
"variable",
"importance",
"effect"
)]
[Package distantia version 2.0.2 Index]