Flexibly shaped distributions can provide a wide variety of shapes within the one distributional form. This makes them useful for data-fitting, modelling and simulation. When we consider distributions via the quantile function, rather than their density or distribution functions, it is possible to see the shape behaviour of some distributions in a richer way.

There are many methods of characterising the properties of a distribution. As well as moments and quantile-based measures of location, scale and shape, there are also L-Moments. L-Moments provide an alternative to moments with the advantage of existing for a wider range of shapes than moments do, and having a easier definition in terms of the quantile function than is the case for moments. This seminar reports on my SSP, including an emphasis on L-Moments for the Generalised Lambda Distributions, with an excursus or two on presentation strategies, social boundaries and R Markdown for reproducible research.