\item{ConvertFun}{[character] names of aggregation functions (e.g. for P[mm], T[deg], Q[mm] : ConvertFun <- c("sum", "mean", "sum"))}
\item{YearFirstMonth}{(optional) [numeric] integer used when NewTimeFormat = "yearly" to set when the starting month of the year (e.g. 01 for calendar year or 09 for hydrological year starting in september)}
\item{YearFirstMonth}{(optional) [numeric] integer used when NewTimeFormat = "yearly" to set when the starting month of the year (e.g. 01 for calendar year or 09 for hydrological year starting in September)}
\item{TimeLag}{(optional) [numeric] numeric indicating a time lag (in seconds) for the time series aggregation (especially useful to aggegate hourly time series in daily time series)}
\item{TimeLag}{(optional) [numeric] numeric indicating a time lag (in seconds) for the time series aggregation (especially useful to aggregate hourly time series in daily time series)}
\item{verbose}{(optional) [boolean] boolean indicating if the function is run in verbose mode or not, default = FALSE}
}
\value{
[POSIXct+numeric] dataframe containing a vector of aggregated dates (POSIXct) and time series values numeric)
[POSIXct+numeric] data.frame containing a vector of aggregated dates (POSIXct) and time series values numeric)
}
\description{
Conversion of time series to another time step (aggregation only). \cr
