35 papers
Tree-Embedded Bayesian Factor Models for Multidimensional Categorical Distributions
Naoki Awaya, Keisuke Sasaki, Genya Kobayashi +1
Analyzing data collected from multiple observational units to estimate common and heterogeneous structures through a hierarchical model is a central task in Bayesian inference, and…
The Covariate-Assisted Bayesian Intransitive Bradley-Terry Model via Combinatorial Hodge Theory
Hisaya Okahara, Tomoyuki Nakagawa, Shonosuke Sugasawa
Pairwise comparison data are widely used to recover latent rankings, yet the models in dominant use assume stochastic transitivity. When preferences are in fact intransitive, a sin…
Information Gap and Feasibility-Aware Inference in Binomial Logistic Mixtures
Yuta Hayashida, Shonosuke Sugasawa
This paper studies the information gap between mixture detection and label recovery in binomial logistic mixtures. Standard likelihood-based criteria such as the Bayesian informati…
Propensity Patchwork Kriging for Scalable Inference on Heterogeneous Treatment Effects
Hajime Ogawa, Shonosuke Sugasawa
Gaussian process-based models are attractive for estimating heterogeneous treatment effects (HTE), but their computational cost limits scalability in causal inference settings. In…
Causal Small Area Estimation with Survey-only Covariates
Tsubasa Ito, Shonosuke Sugasawa
Area-specific causal inference is important in many policy and survey applications, where the goal is to evaluate treatment effects for small geographic or demographic domains. Exi…
Efficient Bayesian Inference in the Cox Model via Rank-Ordered Likelihood
Tomohiro Ohigashi, Shunichiro Orihara, Shonosuke Sugasawa
In Bayesian inference for the Cox proportional hazards model, modeling the baseline hazard function is challenging. Recently, direct Bayesian inference using the partial likelihood…