regspline {pastecs}

Regulation of a time series using splines

Description

Transform an irregular time series in a regular time series, or fill gaps in regular time series using splines

Usage

regspline(x, y=NULL, xmin=min(x), n=length(x),
        deltat=(max(x) - min(x))/(n - 1), rule=1, periodic=FALSE)

Arguments

x

a vector with time in the irregular series. Missing values are allowed

y

a vector of same length as x and holding observations at corresponding times

xmin

allows to respecify the origin of time in the calculated regular time series. By default, the origin is not redefined and it is equivalent to the smallest value in x

n

the number of observations in the regular time series. By default, it is the same number than in the original irregular time series (i.e., length(x)

deltat

the time interval between two observations in the regulated time series

rule

the rule to use for extrapolated values (outside of the range in the initial irregular time series) in the regular time series. With rule=1 (by default), these entries are not calculated and get NA; with rule=2, these entries are extrapolated

periodic

indicates if the time series should be considered as periodic (periodic=TRUE, first value must be equal to the last one). If this is the case, first and second derivates used to calculate spline segments around first and last observations use data in the other extreme of the series. In the other case (periodic=FALSE (by default), derivates for extremes observations are considered to be equal to zero

Details

Missing values are interpolated using cubic splines between observed values.

Value

An object of type 'regul' is returned. It has methods print(), summary(), plot(), lines(), identify(), hist(), extract() and specs().

Note

This function uses spline() for internal calculations. However, interpolated values are not allowed to be higher than the largest initial observation or lower than the smallest one.

Author(s)

Frédéric Ibanez ([e-mail]), Philippe Grosjean ([e-mail])

References

Lancaster, P. & K. Salkauskas, 1986. Curve and surface fitting. Academic Press, England, 280 pp.

See Also

regul, regarea, regconst, reglin, regul.screen, regul.adj, tseries, is.tseries, splinefun

Examples

data(releve)
reg <- regspline(releve$Day, releve$Melosul)
plot(releve$Day, releve$Melosul, type="l")
lines(reg$x, reg$y, col=2)