R: Estimate the dead time between input and output

estimateDelay {hydromad}

R Documentation

Estimate the dead time between input and output

Description

Use cross-correlation to estimate the delay between an input time series and (rises in) the corresponding output time series.

Usage

estimateDelay(DATA = data.frame(U=, Q=), rises = TRUE,
              lag.max = hydromad.getOption("max.delay"),
              n.estimates = 1, negative.ok = FALSE,
              na.action = na.exclude,
              plot = FALSE, main = NULL, ...)

Arguments

`DATA`	a `ts`-like object with named components: `U` input (forcing) time series. `Q` output (response) time series.
`rises`	use only rises in the output to estimate delay.
`lag.max`	largest delay (in time steps) to consider.
`n.estimates`	number of estimates of delay to produce.
`negative.ok`	to allow negative delay times to be considered.
`na.action`	handler for missing values. The default removes leading and trailing NAs only. Use `na.exclude` to remove all NAs, but the result will not be a valid autocorrelation sequence.
`plot`	plot the cross-correlation function.
`main`	title for plot.
`...`	further arguments passed to `ccf` or on to `plot.acf`.

Details

The estimated delay is the one maximising the cross-correlation function.

Value

The estimated delay as an integer number of time steps. If n.estimates > 1, that number of integer delays, ordered by the CCF.

Author(s)

Felix Andrews felix@nfrac.org

Examples

set.seed(1)
x <- ts(pmax(0, rgamma(200, shape=0.1, scale=20) - 5))
## simulate error as multiplicative uniform random
y <- x * runif(200, min=0.5, max=1.5)
## and resample 10 percent of time steps
ii <- sample(seq_along(y), 20)
y[ii] <- rev(y[ii])
## apply recursive filter and lag
y <- filter(y, 0.8, method="r")
y <- lag(y, -2) # true delay is 2
plot(ts.union(y,x))
## based on cross correlation function:
estimateDelay(ts.union(y,x), rises = FALSE, plot = TRUE)
## based on ccf with flow rises only:
estimateDelay(ts.union(y,x), plot = TRUE)

[Package hydromad version 0.9-18 Index]