simulCase: Simulation of nrep disturbance time series.

In RETURN-project/BenchmarkRecovery: Benchmark recovery indicators derived from remote sensing time series

Description

Simulation of nrep disturbance time series.

Usage

simulCase(
  nrep,
  nyr,
  nobsYr,
  nDr,
  seasAv,
  seasAmp,
  trAv,
  remSd,
  distMaglim,
  distTy,
  distReclim,
  mval,
  mvaldist,
  distType
)

Arguments

nrep	number of time series to simulate
nyr	number of years that need to be simulated
nobsYr	number of observations per year that will be simulated
nDr	number of drought years that are introduced [i.e. setting seasonality of a year equal to its minimum value]. These drought years are randomly chosen for each of the simulated time series.
seasAv	average seasonality profile
seasAmp	seasonality amplitude
trAv	offset value of time series
remSd	standard deviation of the remainder
distMaglim	limits of the disturbance magnitude, should be a vector with the minimum and maximum value. If the minimum equals the maximum value, the disturbance magnitude is fixed for each simulated time series (and equal to the minimum value). When the minimum value does not equal the maximum value, a disturbance magnitude is randomly chosen in the given interval for each simulated time series.
distTy	year of the disturbance. If distTy equals one, the disturbance will take place in the first year. The exact disturbance date (day or year) is randomly chosen per time series.
distReclim	limits of the halftime period of the recovery [number of observations], should be a vector with the minimum and maximum value. If the minimum equals the maximum value, the recovery period is fixed for each simulated time series (and equal to the minimum value). When the minimum value does not equal the maximum value, a recovery period is randomly chosen in the given interval for each simulated time series.
mval	number of missing values to be introduced. If mval equals NA, no missing values are introduced. For missing values with a random interval (see mvaldist), this should equal the fraction of missing values (mval equal to 0.1 will result in an NA value for 10 percent of the time series). For missing values having a regular interval, every mval observations one value is kept (eg for a daily time series, a mval equal to 5 will result in one observation every 5 days).
mvaldist	the distribution of the missing values. Should equal 'random'or 'interval'.
distType	the type of disturbance. piecewise refers to a linear decay function, while exponential refers to an exponential decay

Value

a list with the simulated time series, offest, seasonality, remainder, disturbance component and parameters used for the simulation. The time series (components) are stored as matrix where each row is a time series and the columns are associated with the observation numbers.

RETURN-project/BenchmarkRecovery documentation built on July 13, 2021, 5:47 p.m.