Simulate uncertainty in a dataset

Simulate uncertainty in a dataset given an estimate of standard deviation and an ARIMA model

simulateAutoCorrelatedUncertainty(
  n,
  sd,
  mean = 0,
  ar = sqrt(0.5),
  arima.order = c(1, 0, 0),
  seed = NA
)

Arguments

n

length of output vector

sd

standard deviation of the output vector

mean

mean of the output vector

ar

Autocorrelation coefficient to use for modelling uncertainty, what fraction of the uncertainties are autocorrelated? (default = sqrt(0.5); or 50 percent autocorrelated uncertainty)

arima.order

Order to use for ARIMA model used in modelling uncertainty (default = c(1,0,0))

seed

Optionally enter an integer to set a seed for the random number generation

Value

ts simulated from a from an ARIMA model with a defined mean and variance

See also

Other utility: askUser(), concatEnsembleTimeseries(), convertAD2BP(), convertBP2AD(), createChronMeasInputDf(), gaussianize(), generateEnsembleFromUncertainty(), getLastVarString(), getOs(), heuristicUnits(), loadRemote(), pullInstance(), stringifyVariables(), surrogateDataFun()