hfserie: the bended time series. If it is a matrix time series, it has to have the same column names than the hfserie used for the benchmark.
benchmark: a twoStepsBenchmark object, from which the parameters and coefficients are taken.
reeval.smoothed.part: a boolean of length 1. If TRUE, the smoothed part is reevaluated, hence the aggregated benchmarked series is equal to the low-frequency series.
Returns
reUseBenchmark returns an object of class twoStepsBenchmark .
Details
reUseBenchmark is primarily meant to be used on a series that is derived from the previous one, after some modifications that would bias the estimation otherwise. Working-day adjustment is a good example. Hence, by default, the smoothed part of the first model isn't reevaluated ; the aggregated benchmarked series isn't equal to the low-frequency series.