fit_Exptrawl: Fits an exponential trawl function to equidistant time series...

Description Usage Arguments Details Value Examples

View source: R/FitTrawlFunctions.R

Description

Fits an exponential trawl function to equidistant time series data

Usage

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fit_Exptrawl(x, Delta = 1, plotacf = FALSE, lags = 100)

Arguments

x

vector of equidistant time series data

Delta

interval length of the time grid used in the time series, the default is 1

plotacf

binary variable specifying whether or not the empirical and fitted autocorrelation function should be plotted

lags

number of lags to be used in the plot of the autocorrelation function

Details

The trawl function is parametrised by the parameter λ > 0 as follows:

g(x) = e^{λ x}, \mbox{ for } x ≤ 0.

The Lebesgue measure of the corresponding trawl set is given by 1/λ.

Value

lambda: the memory parameter λ in the exponential trawl

LM: the Lebesgue measure of the trawl set associated with the exponential trawl, i.e. 1/λ.

Examples

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#Simulate a univariate trawl process and fit the exponential trawl function
set.seed(1)
t <- 1000
Delta <- 1
v <- 250
lambda <- 0.25
#Simulate a univariate trawl process with exponential trawl function and
#Poisson marginal law
trawl <- sim_UnivariateTrawl(t,Delta,burnin=50,marginal =c("Poi"),trawl
="Exp",v=v, lambda1=lambda)
#Fit the exponential trawl function to the simulated data
fittrawlfct <- fit_Exptrawl(trawl,Delta, plotacf=TRUE,lags=500)
#Print the results
print(paste("lambda: estimated:", fittrawlfct$lambda, ", theoretical:",
lambda))

trawl documentation built on Aug. 16, 2018, 5:04 p.m.