fit_marginalNB: Fist a negative binomial distribution as marginal law
In trawl: Estimation and Simulation of Trawl Processes

Fist a negative binomial distribution as marginal law

1	fit_marginalNB(x, LM, plotdiag = FALSE)

`x`	vector of equidistant time series data
`LM`	Lebesgue measure of the estimated trawl
`plotdiag`	binary variable specifying whether or not diagnostic plots should be provided

The moment estimator for the parameters of the negative binomial distribution are given by

\hat θ = 1-\mbox{E}(X)/\mbox{Var}(X),

and

\hat m = \mbox{E}(X)(1-\hat θ)/(\widehat{ \mbox{LM}} \hat θ).

m: parameter in the negative binomial marginal distribution

theta: parameter in the negative binomial marginal distribution

a: Here a=θ/(1-θ). This is given for an alternative parametrisation of the negative binomial marginal distribution

trawl documentation built on Feb. 23, 2021, 1:06 a.m.

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