ga_check_anomaly: A function to perform Anomaly Detection This is based on...

In IronistM/googleAnalyticsModelR: Provide modelling functionaly for Google Analytics data

Description

A function to perform Anomaly Detection This is based on Twitter's package

Usage

ga_check_anomaly(..., df = NULL, time_col = "date", value_col = NULL,
  title = NULL, anoms = 0.02, direction = direction,
  piecewise_median_period_wk = NULL, y_log = y_log, longterm = NULL)

Arguments

...	extra values to be passed to AnomalyDetection::AnomalyDetectionTs.
df	Data frame
time_col	Column that has time data. We assume this is either 'date', 'datehour“ from Google Analytics API
value_col	Column that has value data
direction	Direction of anomaly. Positive ("posi"), Negative ("neg") or "both".
longterm	Increase anom detection efficacy for time series that are greater than a month. This automatically becomes TRUE if the data is longer than 30 days.
time_unit	Time unit for aggregation.
fun.aggregate	Function to aggregate values.
e_value	Whether expected values should be returned.
na_fill_type	- Type of NA fill: "previous" - Fill with previous non-NA value. "value" - Fill with the value of na_fill_value. "interpolate" - Linear interpolation. "spline" - Spline interpolation. NULL - Skip NA fill. Use this only when you know there is no NA.
na_fill_value	- Value to fill NA when na_fill_type is "value"

IronistM/googleAnalyticsModelR documentation built on May 17, 2019, 1:13 a.m.