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

In tspredit: Time Series Prediction with Integrated Tuning

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(outliers = outliers_boxplot(), nw = 0)

Arguments

outliers	Indicate outliers transformation class. NULL can avoid outliers removal.
nw	windows size

Value

returns a ts_norm_ean object.

Examples

# time series to normalize
library(daltoolbox)
data(tsd)

# convert to sliding windows
ts <- ts_data(tsd$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])

tspredit documentation built on June 22, 2025, 5:07 p.m.