View source: R/transformation.R
fs | R Documentation |
It is useful for linearising the relationship of a seasonal input time series (e.g. solar azimuth, solar elevation, calendar features, ...) to some output (energy consumption, indoor temperatures, ...). It basically decomposes a cyclic time series into a set of sine-cosine components that are used as inputs for the modelling of some output, each of the components linearly depends to the output.
fs(X, featureName, nHarmonics)
X |
<timeSeries> timeSeries containing the series to transform. This series must have a cyclic behaviour (e.g. hour of the day, day of the week, solar azimuth, day of the year, ...) in order to be correctly transformed. Optionally, other variables that are not declared in featuresNames can be bypassed to the output.. |
nHarmonics |
<integer> number of harmonics considered in the Fourier Series. A high number allows to model more precisely the relation, but it considerably increase the cost of computation. The number of harmonics is related with the number of features in the output matrix (2 * nHarmonics) + 1 |
featureNames |
<list> list of strings selecting the series to transform |
<timeSeries> same initial information of data input argument, plus the sine-cosine components of the Fourier Series as new columns
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