tspredit (version 1.2.767)

ts_norm_ean: Adaptive Normalization with EMA

Description

Normalize a time series using exponentially weighted statistics that adapt to distributional changes, optionally after outlier mitigation.

Usage

ts_norm_ean(outliers = outliers_boxplot(), nw = 0)

Value

A ts_norm_ean object.

Arguments

outliers

Indicate outliers transformation class. NULL can avoid outliers removal.

nw

windows size

References

Ogasawara, E., Martinez, L. C., De Oliveira, D., Zimbrão, G., Pappa, G. L., Mattoso, M. (2010). Adaptive Normalization: A novel data normalization approach for non-stationary time series. Proceedings of the International Joint Conference on Neural Networks (IJCNN). doi:10.1109/IJCNN.2010.5596746

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])