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bflSmooth smoothes a time series into a time series of a higher frequency that exactly aggregates into the higher one. The process followed is Boot, Feibes and Lisman, which minimizes the squares of the variations.

Usage

bflSmooth(lfserie, nfrequency, weights = NULL, lfserie.is.rate = FALSE)

Arguments

lfserie

a time series to be smoothed

nfrequency

the new high frequency. It must be a multiple of the low frequency.

weights

NULL or a time series of the same size than the expected high-frequency serie.

lfserie.is.rate

TRUE or FALSE. Only taken into account if weights isn't NULL.

Value

A time series of frequency nfrequency

Details

If weights isn't NULL the results depends of lfserie.is.rate :

  • if FALSE the rate output/weights is smoothed with the constraint that the aggregated output is equal to the input lfserie.

  • if TRUE the input lfserie is the rate to be smoothed, with the constraint that the low-frequency weighted means of the output are equal to lfserie.