Standard_Copula_Sim: Archimedean/elliptic copula model - Simulation

In rjaneUCF/MultiHazard-R-Package: Tools for modeling compound events

Description

Simulating from a fitted Archimedean or elliptic copula model.

Usage

Standard_Copula_Sim(Data, Marginals, Copula, mu = 365.25, N = 10000)

Arguments

Data	Data frame containing n at least partially concurrent time series. First column may be a "Date" object. Can be Dataframe_Combine output.
Marginals	An migpd object containing the n-independent generalized Pareto models.
Copula	An Archimedean or elliptic copula model. Can be specified as an Standard_Copula_Fit object.
mu	(average) Number of events per year. Numeric vector of length one. Default is 365.25, daily data.
N	Number of years worth of extremes to be simulated. Numeric vector of length one. Default 10,000 (years).

Value

Each n-dimensional realisation is given on the transformed [0,1]^n scale (first n columns) in the first data frame u.Sim and on the original scale in the second data frame x.Sim.

See Also

Standard_Copula_Sel Standard_Copula_Fit

Examples

#Fitting multiple independent GPDs to the data
#(required to transform realisation back to origional scale)
S20.Migpd<-Migpd_Fit(Data=S20.Detrend.Declustered.df[,-1],mqu=c(0.975,0.975,0.9676))
#Fitting Gaussian copula
Standard_Copula_Sim(Data=S20.Detrend.df,Marginals=S20.Migpd,Copula=S20.Gaussian,
                    mu=365.25,N=10000)

rjaneUCF/MultiHazard-R-Package documentation built on Jan. 28, 2021, 12:07 a.m.