Pagani, Wiegand and Nadarajah wrote a paper past last Spring on the Rosenbrock distribution. Now, I did not know this distribution under that name but as the banana benchmark distribution I met for the first time in the 1999 Haario, Saksman and Tamminen paper on adaptive MCMC. And that I used in several papers (the picture below being borrowed from Statisfaction!)

The Rosenbrock function was introduced by… Howard Rosenbrock in 1960 in a computer journal as a benchmark for optimisation. (Or by someone else to keep up with Stigler’s Law of Eponymy.) It can be turned into a probability density by exponentiating its opposite. It corresponds to a Normal N(μ,σ²) marginal on the first component, followed by T Normal

N(x²_{t-1},^{σ²}/_{10})

conditional distributions on the following components. It is thus fully known, incl. its normalising constant, and easy to simulate. Hence to use as a fat tail target for benchmarking MCMC algorithms. The authors propose an extension as the hybrid Rosenbrock where several parallel sequences stem from the same component, but it is unclear to me how useful of a generalisation this is…