fit_LMtrawl: Fits a long memory trawl function to equidistant univariate...

Description Usage Arguments Details Value Examples

View source: R/FitTrawlFunctions.R

Description

Fits a long memory trawl function to equidistant univariate time series data

Usage

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fit_LMtrawl(x, Delta = 1, GMMlag = 5, 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

GMMlag

lag length used in the GMM estimation, the default is 5

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 two parameters H> 1 and α > 0 as follows:

g(x) = (1-x/α)^{-H},\mbox{ for } x ≤ 0.

The Lebesgue measure of the corresponding trawl set is given by α/(1-H).

Value

alpha: parameter in the long memory trawl

H: parameter in the long memory trawl

LM: The Lebesgue measure of the trawl set associated with the long memory trawl

Examples

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#Simulate a univariate trawl process and fit the long memory trawl function
set.seed(1)
t <- 1000
Delta <- 1
v <- 250
alpha <- 0.01
H <- 1.3
#Simulate a univariate trawl process with LM trawl function and Poisson
#marginal law
trawl <- sim_UnivariateTrawl(t,Delta,burnin=50,marginal =c("Poi"),trawl
="LM",v=v, alpha=alpha, H=H)
#Fit the LM trawl function to the simulated data
fittrawlfct <- fit_LMtrawl(trawl,Delta, plotacf=TRUE,lags=500)
#Print the results
print(paste("alpha: estimated:", fittrawlfct$alpha, ", theoretical:", alpha))
print(paste("H: estimated:", fittrawlfct$H, ", theoretical:", H))

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