s2scor: Estimation of lag-1 season-to-season correlation coefficients

In itsoukal/anySim: Stochastic Simulation of Processes with any Marginal Distribution and Correlation Structure

Description

Estimation of lag-1 seasson-to-season correlation coefficients.

Usage

s2scor(data)

Arguments

data	A matrix of dimensions k x m, where m denotes the number of sub-seasons and k the number of periods. For instance k may refer to years and m to months (i.e., 12). Another example could regard k as days (e.g., 31 x years) and m to hours (i.e., 24).

Value

A k-dimensional vector with the lag-1 season-to-season correlations coefficients.

Examples

## Simulation of cyclostationary process with 12 seasons and zero-inflated marginal distributions.
rtarget<-c(0.5, 0.7, 0.6, 0.4, 0.5, 0.7, 0.8, 0.7, 0.6, 0.4, 0.5, 0.7)
NumOfSeasons=length(rtarget)
FXs<-rep('qmixed',NumOfSeasons)
PFXs<-vector("list",NumOfSeasons)
PFXs<-lapply(PFXs,function(x) x<-list(p0=0.4, Distr=qexp, rate=0.5))

SPARTApar<-EstSPARTA(s2srtarget = rtarget, dist = FXs, params = PFXs,
NatafIntMethod = 'GH', NoEval = 9, polydeg = 8)

sim<-SimSPARTA(SPARTApar = SPARTApar, steps=100000, stand=0)
s2scor(sim$X)
plot(s2scor(sim$X)); lines(rtarget, col='red')

itsoukal/anySim documentation built on May 7, 2020, 11:57 p.m.