2 citations · 4 across the 5 of their papers we have counts for
4 papers · 1 filter
Robust estimation for Threshold Autoregressive Moving-Average models
Greta Goracci, Davide Ferrari, Simone Giannerini +1
Threshold autoregressive moving-average (TARMA) models are popular in time series analysis due to their ability to parsimoniously describe several complex dynamical features. Howev…
Sparse composite likelihood selection
Claudia Di Caterina, Davide Ferrari
Composite likelihood has shown promise in settings where the number of parameters is large due to its ability to break down complex models into simpler components, thus enablin…
Model Selection Confidence Sets by Likelihood Ratio Testing
Chao Zheng, Davide Ferrari, Yuhong Yang
The traditional activity of model selection aims at discovering a single model superior to other candidate models. In the presence of pronounced noise, however, multiple models are…
Parsimonious and Efficient Likelihood Composition by Gibbs Sampling
Davide Ferrari, Guoqi Qian
The traditional maximum likelihood estimator (MLE) is often of limited use in complex high-dimensional data due to the intractability of the underlying likelihood function. Maximum…