StructuralDecompose: Main decomposition algorithm

In StructuralDecompose: Decomposes a Level Shifted Time Series

Main decomposition algorithm

Description

Main decomposition algorithm

Usage

StructuralDecompose(
  Data,
  frequency = 12,
  break_algorithm = "strucchange",
  smoothening_algorithm = "lowess",
  break_level = 0.05,
  median_level = 0.5,
  mean_level = 0.5,
  level_length = 12,
  conf_level = 0.5,
  window_len = 12,
  plot = FALSE
)

Arguments

Data	Time series required
frequency	Frequency of the tine series
break_algorithm	breakpoints algorithm used. Defaults to strucchange
smoothening_algorithm	Smoothing algorithm used. Defaults to lowess
break_level	Break level for the breakpoints algorithm
median_level	Average median distance between two level
mean_level	Average mean distance between a group of points near breakpoints
level_length	Minimum number of points required to determine a level
conf_level	Confidence level for Anomaly detection, best to keep this a static value
window_len	Length of the Moving window for Anomaly Detection
plot	True of False indicating if you want the internal plots to be generated

Value

The decomposed time series along with a host of other metrics

Examples

StructuralDecompose(Data = StructuralDecompose::Nile_dataset[,1])

StructuralDecompose(Data = runif(n = 50, min = 1, max = 10))

StructuralDecompose documentation built on Feb. 16, 2023, 9:46 p.m.