ts_norm_ean: Time Series Adaptive Normalization (Exponential Moving...

In daltoolbox: Leveraging Experiment Lines to Data Analytics

Time Series Adaptive Normalization (Exponential Moving Average - EMA)

Description

Creates a normalization object for time series data using an Exponential Moving Average (EMA) method. This normalization approach adapts to changes in the time series and optionally removes outliers.

Usage

ts_norm_ean(remove_outliers = TRUE, nw = 0)

Arguments

remove_outliers	logical: if TRUE (default) outliers will be removed.
nw	windows size

Value

returns a ts_norm_ean object.

Examples

# time series to normalize
data(sin_data)

# convert to sliding windows
ts <- ts_data(sin_data$y, 10)
ts_head(ts, 3)
summary(ts[,10])

# normalization
preproc <- ts_norm_ean()
preproc <- fit(preproc, ts)
tst <- transform(preproc, ts)
ts_head(tst, 3)
summary(tst[,10])

daltoolbox documentation built on Nov. 3, 2024, 9:06 a.m.