Exponential Moving Average over a Data Stream

Applies an exponential moving average to components of a data stream.

Usage

DSF_ExponentialMA(dsd = NULL, dim = NULL, alpha = 0.5)

Arguments

dsd

The input stream as an DSD object.

dim

Columns to which the filter is applied. The default is all columns.

alpha

Smoothing coefficient in \([0, 1]\). Larger values discount older observations faster.

Value

An object of class DSF_ExponentialMA (subclass of DSF and DSD).

Details

The exponential moving average is calculated by:

\(S_t = \alpha Y_t + (1 - \alpha)\; S_{i-1}\)

with \(S_0 = Y_0\).

See also

Other DSF: DSF(), DSF_Convolve(), DSF_Downsample(), DSF_FeatureSelection(), DSF_Func(), DSF_Scale(), DSF_dplyr()

Author

Michael Hahsler

Examples

# Smooth a time series
data(presidents)

stream <- data.frame(
    presidents,
    .time = time(presidents)) %>%
  DSD_Memory()

plot(stream, dim = 1, n = 120, method = "ts", main = "Original")


smoothStream <- stream %>% DSF_ExponentialMA(alpha = .7)
smoothStream
#> Memorized Stream
#> + exponential MA(0.7) 
#> Class: DSF_ExponentialMA, DSF, DSD_R, DSD 

reset_stream(smoothStream)
plot(smoothStream, dim = 1, n = 120, method = "ts", main = "With ExponentialMA(.7)")