bootjack function

Bootstrap-jacknife of flow calibration statistics

bootjack(
  flows,
  GOF_stat = c("NSE", "KGE"),
  nSample = 1000,
  waterYearMonth = 10,
  startYear = NULL,
  endYear = NULL,
  minDays = 100,
  minYears = 10,
  returnSamples = FALSE,
  seed = NULL,
  bootYearFile = NULL
)

Arguments

• flows: Required. Data frame containing the date, observed and simulated flows. The variable names must be date , obs , and sim , respectively. The date must be a standard date.

• GOF_stat: Required. Name(s) of simulation goodness of fit statistic(s) to be calculated. Currently both NSE and KGE are supported.

• nSample: Required. Number of samples for bootstrapping.

• waterYearMonth: Required. Month of beginning of water year. Default is 10 (October). If the calendar year is required, set waterYearMonth = 13.

• startYear: Optional. First year of data to be used. If NULL

  then not used.

• endYear: Optional. Last year of data to be used. If NULL then not used.

• minDays: Required. Minimum number of days per year with valid (i.e. greater than 0) flows. Default is 100.

• minYears: Required. Minimum number years to be used. Default is 10.

• returnSamples: Optional. Default is FALSE. If TRUE, then sample statistics are returned. This is primarily used for debugging/testing.

• seed: Optional. If NULL (the default) then no seed is specified for the random number generator used for the bootstrapping. If a value is specified then the bootstrapping will always use the same set of pseudo-random numbers.

• bootYearFile: Optional. If NULL (the default) the years used for the bootstrapping are neither output nor input. If a file is specified, and it it does not already exist, then the bootstrap years will be written to a .csv file as a table with the dimensions of years x nSample. If a file is specified, and it does exist, then the years will be read in, and used for the bootstrapping.

Returns

Returns a data frame containing the goodness of fit statistic name (i.e. NSE and/or KGE ), and seJack = standard error of jacknife, seBoot = standard error of bootstrap, p05, p50, p95, the 5th, 50th and 95th percentiles of the estimates, score = jackknife score, biasJack = bias of jackknife, biasBoot = bias of bootstap, seJab = standard error of jackknife after bootstrap.

Examples

NSE_stats <- bootjack(flows_1030500, "NSE")

See Also

read_CAMELS

Author(s)

Martyn Clark and Kevin Shook