transform_data: Apply different transformations to the original series

In pridiltal/oddwater: Outlier Detection in Data from Water-Quality Sensors

Description

This function apply different transformations to the original variables. This data preprocessing step was incorporated with the aim of highlighting different types of anomalies such as sudden isolated spikes, sudden isolated drops, sudden shifts, impossible values (negative values) and out of range values etc

Usage

transform_data(data, time_bound = 90, regular = FALSE,
  time_col = "Timestamp")

Arguments

data	A dataframe. This dataframe contains a seperate column for Timestamp, in addition to the variables that need to be transformed
time_bound	A positive constant. This is to reduce the effect coming from too small time gaps when calculating derivatives.
regular	Regular time interval (TRUE) or irregular (FALSE)
time_col	A quoted string to specify the column name of the timestamp

Value

A tsibble object with the original and the transformed series

Author(s)

Priyanga Dilini Talagala

Examples

data <- data_sandy_anom[,c("Timestamp", "Cond", "Tur", "Level")]
data <- tidyr::drop_na(data)
trans_data <- oddwater::transform_data(data)

pridiltal/oddwater documentation built on Dec. 18, 2019, 8:18 p.m.