21 citations · 90 across the 97 of their papers we have counts for
14 papers · 1 filter
Repulsive g-Priors for Regression Mixtures
Yuta Hayashida, Shonosuke Sugasawa
Mixture regression models are powerful tools for capturing heterogeneous covariate-response relationships, yet classical finite mixtures and Bayesian nonparametric alternatives oft…
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…
Robust Global Fr'echet Regression via Weight Regularization
Hao Li, Shonosuke Sugasawa, Shota Katayama
The Fréchet regression is a useful method for modeling random objects in a general metric space given Euclidean covariates. However, the conventional approach could be sensitive to…
On Misspecified Error Distributions in Bayesian Functional Clustering: Consequences and Remedies
Fumiya Iwashige, Tomoya Wakayama, Shonosuke Sugasawa +1
Nonparametric Bayesian approaches provide a flexible framework for clustering without pre-specifying the number of groups, yet they are well known to overestimate the number of clu…
Efficient Prior Sensitivity and Tipping-point Analysis for Medical Research: Revisiting Sampling Importance Resampling
Tomohiro Ohigashi, Shonosuke Sugasawa
Bayesian methods have received increasing attention in medical research, where sensitivity analysis of prior distributions is essential. Such analyses typically require the evaluat…
Noise-Robust Phase Connectivity Estimation via Bayesian Circular Functional Models
Shonosuke Sugasawa, Takeru Matsuda, Tomoyuki Nagakawa
The phase locking value (PLV) is a widely used measure to detect phase connectivity. Main drawbacks of the standard PLV are it can be sensitive to noisy observations and does not p…
Causal Inference under Threshold Manipulation: Bayesian Mixture Modeling and Heterogeneous Treatment Effects
Kohsuke Kubota, Shonosuke Sugasawa
Many marketing applications, including credit card incentive programs, offer rewards to customers who exceed specific spending thresholds to encourage increased consumption. Quanti…
Robust Spatio-Temporal Distributional Regression
Tomotaka Momozaki, Shonosuke Sugasawa, Tomoyuki Nakagawa +2
Motivated by investigating spatio-temporal patterns of the distribution of continuous variables, we consider describing the conditional distribution function of the response variab…
Outlier-Robust Bayesian Multivariate Analysis with Correlation-Intact Sandwich Mixture
Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
Handling outliers is a fundamental challenge in multivariate data analysis because outliers may distort the structures of correlation or conditional independence. Although robust B…
Sequential Adaptive Priors for Orthogonal Functions
Shonosuke Sugasawa, Daichi Mochihashi
We propose a novel class of prior distributions for sequences of orthogonal functions, which are frequently required in various statistical models such as functional principal comp…
Scalable Estimation of Crossed Random Effects Models via Multi-way Discretization
Shota Takeishi, Shonosuke Sugasawa
Cross-classified data frequently arise in scientific fields such as education, healthcare, and social sciences. A common modeling strategy is to introduce crossed random effects wi…
Bayesian Doubly Robust Causal Inference via Posterior Coupling
Shunichiro Orihara, Tomotaka Momozaki, Shonosuke Sugasawa
Bayesian doubly robust (DR) causal inference faces a fundamental dilemma: joint modeling of outcome and propensity score suffers from the feedback problem where outcome information…
Robust Bayesian Inference for Censored Survival Models
Yasuyuki Hamura, Takahiro Onizuka, Shintaro Hashimoto +1
This paper proposes a robust Bayesian accelerated failure time model for censored survival data. We develop a new family of life-time distributions using a scale mixture of the gen…
Bayesian Time-Varying Meta-Analysis via Hierarchical Mean-Variance Random-effects Models
Kohsuke Kubota, Shonosuke Sugasawa, Keiichi Ochiai +1
Meta-analysis is widely used to integrate results from multiple experiments to obtain generalized insights. Since meta-analysis datasets are often heteroscedastic due to varying su…