An ARFIMA-based model for daily precipitation amounts with direct access to fluctuations
Sign Up to like & getrecommendations! Published in 2020 at "Stochastic Environmental Research and Risk Assessment"
DOI: 10.1007/s00477-020-01833-w
Abstract: Correlations in models for daily precipitation are often generated by elaborate numerics that employ a high number of hidden parameters. We propose a parsimonious and parametric stochastic model for European mid-latitude daily precipitation amounts with… read more here.
Keywords: effective sample; model; sample size; precipitation amounts ... See more keywords
Discussion on "Predictively consistent prior effective sample sizes," by Beat Neuenschwander, Sebastian Weber, Heinz Schmidli, and Anthony O'Hagan.
Sign Up to like & getrecommendations! Published in 2020 at "Biometrics"
DOI: 10.1111/biom.13254
Abstract: Neuenschwander et al. address a seemingly easy but often complicated problem in applied Bayesian methodology. We discuss some issues that relate to the question of why one might care about the effective sample size ( E… read more here.
Keywords: sample; discussion predictively; effective sample; prior effective ... See more keywords
Locally Scaled and Stochastic Volatility Metropolis- Hastings Algorithms
Sign Up to like & getrecommendations! Published in 2021 at "Algorithms"
DOI: 10.3390/a14120351
Abstract: Markov chain Monte Carlo (MCMC) techniques are usually used to infer model parameters when closed-form inference is not feasible, with one of the simplest MCMC methods being the random walk Metropolis–Hastings (MH) algorithm. The MH… read more here.
Keywords: stochastic volatility; volatility metropolis; metropolis hastings; effective sample ... See more keywords