momentum_aggregate: Aggregate 'momentum()' Data Frames Across Parameter...

In distantia: Advanced Toolset for Efficient Time Series Dissimilarity Analysis

Aggregate momentum() Data Frames Across Parameter Combinations

Description

The function momentum() allows variable importance assessments based on several combinations of arguments at once. For example, when the argument distance is set to c("euclidean", "manhattan"), the output data frame will show two importance scores for each pair of compared time series and variable, one based on euclidean distances, and another based on manhattan distances.

This function computes importance stats across combinations of parameters.

If there are no different combinations of arguments in the input data frame, no aggregation happens, but all parameter columns are removed.

Usage

momentum_aggregate(df = NULL, f = mean, ...)

Arguments

df	(required, data frame) Output of momentum(), momentum_ls(), or momentum_dtw(). Default: NULL
f	(optional, function) Function to summarize psi scores (for example, mean) when there are several combinations of parameters in df. Ignored when there is a single combination of arguments in the input. Default: mean
...	(optional, arguments of f) Further arguments to pass to the function f.

Value

data frame

See Also

Other momentum_support: momentum_boxplot(), momentum_model_frame(), momentum_spatial(), momentum_stats(), momentum_to_wide()

Examples

#three time series
#climate and ndvi in Fagus sylvatica stands in Spain, Germany, and Sweden
tsl <- tsl_initialize(
  x = fagus_dynamics,
  name_column = "name",
  time_column = "time"
) |>
  tsl_transform(
    f = f_scale_global
  )

if(interactive()){
  tsl_plot(
    tsl = tsl,
    guide_columns = 3
    )
}

#momentum with multiple parameter combinations
#-------------------------------------
df <- momentum(
  tsl = tsl,
  distance = c("euclidean", "manhattan"),
  lock_step = TRUE
)

df[, c(
  "x",
  "y",
  "distance",
  "importance"
)]

#aggregation using means
df <- momentum_aggregate(
  df = df,
  f = mean
)

df

distantia documentation built on April 4, 2025, 5:42 a.m.