UKFE (version 1.0.2)

SimData: Data simulator

Description

Simulation of a random sample from the generalised extreme value, generalised logistic, Gumbel, Kappa3, or generalised Pareto distributions

Usage

SimData(n, pars = NULL, dist = "GenLog", GF = NULL)

Value

A random sample of size n for the chosen distribution.

Arguments

n

sample size to be simulated

pars

vector of parameters in the order of location, scale, shape (only location and shape for Gumbel)

dist

choice of distribution. Either "GEV", "GenLog", "Gumbel", "Kappa3", or "GenPareto"

GF

vector of GF inputs in the order of Lcv, LSkew, QMED (only Lcv and QMED if dist = "Gumbel")

Author

Anthony Hammond

Details

The simulated sample can be generated using the distribution parameters (pars) location, scale and shape, or the growth factor (GF) inputs linear coefficient of variation (Lcv), linear skewness (LSkew) & median annual maximum (QMED). This function applies a probability distribution model which assumes that the sample data is independent and identical, i.e. the assumption is that all observations in the sample would not impact or depend on any other. Furthermore, all observations are from the same underlying process which has not changed over the period of record (stationarity).

Examples

# Simulate a sample of size 30 from a GenLog distribution with parameters 299, 51, -0.042
SimData(30, pars = c(299, 51, -0.042), dist = "GenLog")

# Now simulate using the Lcv, Lskew, and median (0.17, 0.04, 310)
SimData(30, GF = c(0.17, 0.04, 310), dist = "GenLog")