Generalised Additive Extreme Value Models
Scatter plot, with variable-based point colours
Bind a list a data frames
Fitting generalised additive extreme-value family models
Estimate extremal index using `intervals' method
Extract Model Fitted Values
Log-likelihood, AIC and BIC from a fitted evgam object
Moore-Penrose pseudo-inverse of a matrix
Plot a fitted evgam object
Predictions from a fitted evgam object
Print a fitted evgam object
Quantile estimation of a composite extreme value distribution
Running maximum
More Sequence Generation
Simulations from a fitted evgam object
Summary method for a fitted evgam object
Methods for fitting various extreme value distributions with parameters of generalised additive model (GAM) form are provided. For details of distributions see Coles, S.G. (2001) <doi:10.1007/978-1-4471-3675-0>, GAMs see Wood, S.N. (2017) <doi:10.1201/9781315370279>, and the fitting approach see Wood, S.N., Pya, N. & Safken, B. (2016) <doi:10.1080/01621459.2016.1180986>. Details of how evgam works and various examples are given in Youngman, B.D. (2022) <doi:10.18637/jss.v103.i03>.