pTMPS: Apply the TMPS model for a typewise statistical estimate of...

In PhilippBuehler/FloodR: Separation and typing of flood events and typewise staistical return periods (TMPS)

Apply the TMPS model for a typewise statistical estimate of return periods as well as a combined TMPS return period. See also reference Fischer (2018).

Description

Apply the TMPS model for a typewise statistical estimate of return periods as well as a combined TMPS return period. See also reference Fischer (2018).

Usage

pTMPS(
  q = c(10, 100, 1000),
  Flood_events,
  Daily_discharge,
  return_TMPS = c("TMPS", "R1", "R2", "R3", "S1", "S2"),
  Threshold_Q = 3,
  p_as_annuality = TRUE
)

Arguments

q	The quantiles for which the return periods should be calculated Defaults to: 20, 100, 1000
Flood_events	data.frame: Floods events with the columns "Peak_date" (Date format), "HQ" (numeric) and "Type" (factor)
Daily_discharge	data.frame: Daily discharge (continuous) with columns "Date (Date format) and "Discharge" (numeric)
return_TMPS	character vector: What should be returned. Any combination of "TMPS" and the occuring floodtypes
Threshold_Q	numeric: Peak of Threshold, defaults to 3
p_as_annuality	logical: Should all probabilities be treated as an annuality [in years] instead of dimensionless values between 0 and 1

Author(s)

Svenja Fischer

Philipp Bühler

References

Fischer, S. (2018). A seasonal mixed-POT model to estimate high flood quantiles from different event types and seasons. Journal of Applied Statistics, 45(15), 2831–2847. https://doi.org/10.1080/02664763.2018.1441385

PhilippBuehler/FloodR documentation built on March 2, 2024, 9:53 a.m.