- x
a vector with times corresponding to the observations in the irregular initial time series

- weight
a vector of the same length as `x`

, with the weight to give to each observation. A value of 0 indicates to ignore an observation. A value of 1 gives a normal weight to an observation. A higher value gives more importance to the corresponding observation. You can increase weight of observations around major peaks and pits, to make sure they are not lost in the regulated time series. If `weight=NULL`

(by default), then a weight of 1 is used for all observations

- xmin
a vector with all time values for the first observation in the regulated time series to be tested

- frequency
a vector with all the frequencies to be screened

- deltat
a vector with all time intervals to screen. `deltat`

is the inverse of `frequency`

. Only one of these two arguments is required. If both are provided, `frequency`

supersedes `deltat`

- tol
it is possible to tolerate some differences in the time between two matching observations (in the original irregular series and in the regulated series). If `tol=0`

both values must be strictly identical; a higher value allows some fuzzy matching. `tol`

must be a round fraction of `deltat`

and cannot be higher than it, otherwise, it is adjusted to the closest acceptable value. By default, `tol=deltat/5`

- tol.type
the type of window to use for the time-tolerance: `"left"`

, `"right"`

, `"both"`

(by default) or `"none"`

. If `tol.type="left"`

, corresponding `x`

values are seeked in a window ]xregul-tol, xregul]. If `tol.type="right"`

, they are seeked in the window [xregul, xregul+tol[. If `tol.type="both"`

, then they are seeked in the window ]xregul-tol, xregul+tol]. If several observations are in this window, the closest one is used. Finally, if `tol.type="none"`

, then *all* observations in the regulated time series are interpolated (even if exactly matching observations exist!)