View source: R/Con_Sampling_2D.R
Con_Sampling_2D | R Documentation |
Creates a data frame where the declustered excesses of a (conditioning) variable are paired with co-occurences of another variable.
Con_Sampling_2D(Data_Detrend, Data_Declust, Con_Variable, u = 0.97, Thres = NA)
Data_Detrend |
Data frame containing two at least partially concurrent time series, detrended if necessary. Time steps must be equally spaced, with missing values assigned |
Data_Declust |
Data frame containing two (independently) declustered at least partially concurrent time series. Time steps must be equally spaced, with missing values assigned |
Con_Variable |
Column number (1 or 2) or the column name of the conditioning variable. Default is |
u |
Threshold, as a quantile of the observations of the conditioning variable. Default is |
Thres |
Threshold expressed on the original scale of the observations. Only one of |
List comprising the specified Threshold
as the quantile of the conditioning variable above which declustered excesses are paired with co-occurences of the other variable, the resulting two-dimensional sample data
and name
of the conditioning variable. The index of the input dataset that correspond to the events in the conditonal sample x.con
are also provided.
S20.Rainfall<-Con_Sampling_2D(Data_Detrend=S20.Detrend.df[,-c(1,4)],
Data_Declust=S20.Detrend.Declustered.df[,-c(1,4)],
Con_Variable="Rainfall",Thres=0.97)
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