Pareto smoothed importance sampling (PSIS) and PSIS leave-one-out cross-validation for Matlab/Octave
These m-files implement Pareto smoothed importance sampling (PSIS) and PSIS leave-one-out cross-validation for Matlab and Octave
- 'psislw.m' - Pareto smoothed importance sampling smoothing of the log importance weights
- Aki Vehtari and Andrew Gelman (2015). Pareto smoothed importance sampling. arXiv preprint arXiv:1507.02646
- 'psisloo.m' - Pareto smoothed importance sampling leave-one-out log predictive densities
- Aki Vehtari, Andrew Gelman and Jonah Gabry (2015). Efficient implementation of leave-one-out cross-validation and WAIC for evaluating fitted Bayesian models.
- 'gpdfitnew.m' - Estimate the paramaters for the Generalized Pareto Distribution
- Jin Zhang & Michael A. Stephens (2009) A New and Efficient Estimation Method for the Generalized Pareto Distribution, Technometrics, 51:3, 316-325, DOI: 10.1198/tech.2009.08017
Corresponding R code can be found in R package called `loo' which is also available in CRAN.