CorIrregTimser: CorIrregTimser

Description Usage Arguments Examples

View source: R/CorIrregTimser.R

Description

estimating the time scale dependent correlation of irregularly sampled time series

Usage

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CorIrregTimser(timser1, timser2, detr, method = c("InterpolationMethod",
  "DirectFiltering", "IntegrandInterpolationMethod"),
  appliedFilter = c("gauss", "runmean", "lowpass"), fc, tn = seq(from = 10,
  to = max(c(index(timser1), index(timser2))), by = 10), dt,
  int.method = c("linear", "nearest"), k = 5, filt.output)

Arguments

timser1, timser2

time series (zoo-objects)

detr

TRUE for removing a linear trend, else FALSE

method

method to handle irregularity of sampling (DirectFiltering, IntegrandInterpolationMethod, InterpolationMethod)

appliedFilter

time domain filter (gauss, runmean, lowpass)

fc

cut-off frequency of the applied filter

tn

output vector (time) of the filtered data (only used in case of DirectFiltering and IntegrandInterpolationMethod)

dt

regular inter-observation time step of the interpolation (only used in case of InterpolationMethod)

int.method

kind of interpolation (linear, nearest neighbor) (only used in case of InterpolationMethod)

k

scaling factor to define the sharpness of the lowpass

filt.output

TRUE for returning correlation ($cor) and filter results ($ft1, $ft2), FALSE for only returning correlation

Examples

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timeseries1 <- zoo(rnorm(100), order.by=sort(runif(100,min=1,max=1000)))
timeseries2 <- zoo(rnorm(100), order.by=sort(runif(100,min=1,max=1000)))
CorIrregTimser(timser1=timeseries1, timser2=timeseries2, detr=FALSE, method="InterpolationMethod", appliedFilter="gauss", fc=1/200, tn=NA, dt=10, int.method="linear", k=NA, filt.output=TRUE)

EarthSystemDiagnostics/corit documentation built on May 29, 2019, 1:39 p.m.