dot-stretch_re: Use time warping to reduce the number of observations in a...
In tssim: Simulation of Daily and Monthly Time Series

Description Usage Arguments Details Value Author(s) References

Reduce the number of observations in a month using time warping / stretching. Only relevant if a daily time series is simulated

1	.stretch_re(seas_component)

seas_component

Seasonal component for day-of-the-month

Usually time warping would be used to stretch the number of observations of a time series in a given interval to more observations. Here it is used to reduce the number of observations (31) to the number of days in a given month while maintaining the underlying trajectory of the data. This is done by first creating a very long time series for each month, interpolating missing values by spline interpolation and then reducing the number of observations to the number suitable for a given month.

Returns a xts time series containing the day-of-the-month effect.

Daniel Ollech

Ollech, D. (2021). Seasonal adjustment of daily time series. Journal of Time Series Econometrics. doi: 10.1515/jtse-2020-0028

tssim documentation built on June 25, 2021, 5:06 p.m.