paa {jmotif}

Computes a Piecewise Aggregate Approximation (PAA) for a time series.

Description

Computes a Piecewise Aggregate Approximation (PAA) for a time series.

Usage

paa(ts, paa_num)

Arguments

ts

a timeseries to compute the PAA for.

paa_num

the desired PAA size.

References

Keogh, E., Chakrabarti, K., Pazzani, M., Mehrotra, S., Dimensionality reduction for fast similarity search in large time series databases. Knowledge and information Systems, 3(3), 263-286. (2001)

Examples

x = c(-1, -2, -1, 0, 2, 1, 1, 0)
x_paa3 = paa(x, 3)
#
plot(x, type = "l", main = c("8-points time series and its PAA transform into three points",
                          "PAA shown schematically in blue"))
points(x, pch = 16, lwd = 5)
#
paa_bounds = c(1, 1+7/3, 1+7/3*2, 8)
abline(v = paa_bounds, lty = 3, lwd = 2, col = "cornflowerblue")
segments(paa_bounds[1:3], x_paa3, paa_bounds[2:4], x_paa3, col = "cornflowerblue", lwd = 2)
points(x = c(1, 1+7/3, 1+7/3*2) + (7/3)/2, y = x_paa3, pch = 15, lwd = 5, col = "cornflowerblue")