opt_auto {cylcop}

Automatically Find the Best Fitting Copula

Description

The parameters of 15 different circular-linear copulas are fitted to data and sorted according to AIC. For each copula, first, a starting value for the maximum likelihood estimation (MLE) is found using fit_cylcop_cor(). Then, MLE is carried out with a "reasonable" setup using fit_cylcop_ml(). If MLE fails, parameters obtained with fit_cylcop_cor() are reported.

Usage

opt_auto(theta, x)

Arguments

theta

numeric vector of angles (measurements of a circular variable).

x

numeric vector of step lengths (measurements of a linear variable).

Value

A list containing 3 lists: Descriptions of the copulas, the 'cyl_copula' objects with fitted parameters, and the AIC. The lists are sorted by ascending AIC. If fit_cylcop_ml() has failed, the reported parameters are the ones obtained with fit_cylcop_cor() and the AIC is set to NA.

References

Hodel FH, Fieberg JR (2022). “Circular-Linear Copulae for Animal Movement Data.” Methods in Ecology and Evolution. doi:10.1111/2041-210X.13821.

Hodel FH, Fieberg JR (2021). “Cylcop: An R Package for Circular-Linear Copulae with Angular Symmetry.” bioRxiv. doi:10.1101/2021.07.14.452253, https://www.biorxiv.org/content/10.1101/2021.07.14.452253v3/.

See Also

fit_cylcop_cor(), fit_cylcop_ml()

Examples

set.seed(123)

#Optimal copula is independent of marginals.
data <- rcylcop(100,cyl_quadsec(0.1))

#This takes a few seconds to run.
copula_lst <- opt_auto(theta = data[,1], x = data[,2])