interpolate_gaps {chillR} | R Documentation |
Linear gap interpolation
Description
This function linearly interpolates gaps in data series, such as daily temperature records.
Usage
interpolate_gaps(x)
Arguments
x |
a numeric vector, or a vector that can be coerced with as.numeric. Missing values are either NA or non-numeric values. |
Details
The function returns a list with two elements: interp is a new vector, in which all gaps in x have been linearly interpolated. missing is a second vector, which contains information on which values were filled in by interpolation.
Value
interp |
numeric vector, in which all gaps in x have been linearly interpolated |
missing |
boolean vector of the same length as interp and x, which marks all gaps in x as TRUE |
Author(s)
Eike Luedeling
References
Luedeling E, Kunz A and Blanke M, 2013. Identification of chilling and heat requirements of cherry trees - a statistical approach. International Journal of Biometeorology 57,679-689.
Examples
weather<-make_all_day_table(KA_weather)
Tmin_int<-interpolate_gaps(KA_weather[,"Tmin"])
weather[,"Tmin"]<-Tmin_int$interp
weather[,"Tmin_interpolated"]<-Tmin_int$missing
Tmax_int<-interpolate_gaps(KA_weather[,"Tmax"])
weather[,"Tmax"]<-Tmax_int$interp
weather[,"Tmax_interpolated"]<-Tmax_int$missing
#this function is integrated into the fix_weather function, but it can also be run on its own.