detect_anoms: Detects anomalies in a time series using S-H-ESD.
In ivanliu1989/RQuant: A collection of generic functions

Detects anomalies in a time series using S-H-ESD.

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detect_anoms(data, k = 0.49, alpha = 0.05, num_obs_per_period = NULL,
  use_decomp = TRUE, use_esd = FALSE, one_tail = TRUE,
  upper_tail = TRUE, verbose = FALSE)

`data`	Time series to perform anomaly detection on.
`k`	Maximum number of anomalies that S-H-ESD will detect as a percentage of the data.
`alpha`	The level of statistical significance with which to accept or reject anomalies.
`num_obs_per_period`	Defines the number of observations in a single period, and used during seasonal decomposition.
`use_decomp`	Use seasonal decomposition during anomaly detection.
`use_esd`	Uses regular ESD instead of hybrid-ESD. Note hybrid-ESD is more statistically robust.
`one_tail`	If TRUE only positive or negative going anomalies are detected depending on if upper_tail is TRUE or FALSE.
`upper_tail`	If TRUE and one_tail is also TRUE, detect only positive going (right-tailed) anomalies. If FALSE and one_tail is TRUE, only detect negative (left-tailed) anomalies.
`verbose`	Additionally printing for debugging.