Veronica Ballerini
@vballerini.bsky.social
Research associate @harvard.edu @hsph.harvard.edu Dept of Biostatistics | Bayesian causal inference
New on Bluesky 🦋
New on Bluesky 🦋
Do you follow @spletters.bsky.social ?
@alecasa.bsky.social and Davide Ferrari (@unibz.bsky.social) tackle the problem of selecting the number of components in Gaussian mixture models, where traditional single-model criteria like BIC often overlook model selection uncertainty.
Learn more⤵️
www.sciencedirect.com/science/arti...
Learn more⤵️
www.sciencedirect.com/science/arti...
August 11, 2025 at 4:35 PM
Do you follow @spletters.bsky.social ?
I'm truly happy to share with this community 🦋 that our paper is finally out!
If you wanna know more about novel uses of Fisher's Noncentral Hypergeometric distribution and how to make Bayesian inference on its parameters ⤵️⤵️⤵️
Thanks to JSSAM for the journey!
If you wanna know more about novel uses of Fisher's Noncentral Hypergeometric distribution and how to make Bayesian inference on its parameters ⤵️⤵️⤵️
Thanks to JSSAM for the journey!
New article alert! "Inferring a Population Composition From Survey Data With Nonignorable Nonresponse: Borrowing Information From External Sources" by Veronica Ballerini and Brunero Liseo
@vballerini.bsky.social
doi.org/10.1093/jssa...
@vballerini.bsky.social
doi.org/10.1093/jssa...
Inferring a Population Composition From Survey Data With Nonignorable Nonresponse: Borrowing Information From External Sources
Abstract. We introduce a method for inference on the composition of a heterogeneous population using survey data, accounting for the possibility that captu
doi.org
December 12, 2024 at 3:03 PM
I'm truly happy to share with this community 🦋 that our paper is finally out!
If you wanna know more about novel uses of Fisher's Noncentral Hypergeometric distribution and how to make Bayesian inference on its parameters ⤵️⤵️⤵️
Thanks to JSSAM for the journey!
If you wanna know more about novel uses of Fisher's Noncentral Hypergeometric distribution and how to make Bayesian inference on its parameters ⤵️⤵️⤵️
Thanks to JSSAM for the journey!