Fist a negative binomial distribution as marginal law
fit_marginalNB(x, LM, plotdiag = FALSE)vector of equidistant time series data
Lebesgue measure of the estimated trawl
binary variable specifying whether or not diagnostic plots should be provided
m: parameter in the negative binomial marginal distribution
theta: parameter in the negative binomial marginal distribution
a: Here \(a=\theta/(1-\theta)\). This is given for an alternative parametrisation of the negative binomial marginal distribution
The moment estimator for the parameters of the negative binomial distribution are given by $$\hat \theta = 1-\mbox{E}(X)/\mbox{Var}(X),$$ and $$\hat m = \mbox{E}(X)(1-\hat \theta)/(\widehat{ \mbox{LM}} \hat \theta).$$