21 citations · 90 across the 97 of their papers we have counts for
10 papers · 1 filter
Semiparametric Copula Estimation for Spatially Correlated Multivariate Mixed Outcomes: Analyzing Visual Sightings of Fin Whales from a Line Transect Survey
Tomotaka Momozaki, Tomoyuki Nakagawa, Shonosuke Sugasawa +1
For marine biologists, ascertaining the dependence structures between marine species and marine environments, such as sea surface temperature and ocean depth, is imperative for def…
Nonparametric Bayesian Adjustment of Unmeasured Confounders in Cox Proportional Hazards Models
Shunichiro Orihara, Shonosuke Sugasawa, Tomohiro Ohigashi +2
In observational studies, unmeasured confounders present a crucial challenge in accurately estimating desired causal effects. To calculate the hazard ratio (HR) in Cox proportional…
Hierarchical Regression Discontinuity Design: Pursuing Subgroup Treatment Effects
Shonosuke Sugasawa, Takuya Ishihara, Daisuke Kurisu
Regression discontinuity design (RDD) is widely adopted for causal inference under intervention determined by a continuous variable. While one is interested in treatment effect het…
An Unbiased Predictor for Skewed Response Variable with Measurement Error in Covariate
Sepideh Mosaferi, Malay Ghosh, Shonosuke Sugasawa
We introduce a new small area predictor when the Fay-Herriot normal error model is fitted to a logarithmically transformed response variable, and the covariate is measured with err…
Predicting COVID-19 hospitalisation using a mixture of Bayesian predictive syntheses
Genya Kobayashi, Shonosuke Sugasawa, Yuki Kawakubo +2
This paper proposes a novel methodology called the mixture of Bayesian predictive syntheses (MBPS) for multiple time series count data for the challenging task of predicting the nu…
Similarity-based Random Partition Distribution for Clustering Functional Data
Tomoya Wakayama, Shonosuke Sugasawa, Genya Kobayashi
Random partition distribution is a crucial tool for model-based clustering. This study advances the field of random partition in the context of functional spatial data, focusing on…
Bayesian Causal Synthesis for Meta-Inference on Heterogeneous Treatment Effects
Shonosuke Sugasawa, Kosaku Takanashi, Kenichiro McAlinn +1
The estimation of heterogeneous treatment effects in the potential outcome setting is biased when there exists model misspecification or unobserved confounding. As these biases are…
Posterior Robustness with Milder Conditions: Contamination Models Revisited
Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
Robust Bayesian linear regression is a classical but essential statistical tool. Although novel robustness properties of posterior distributions have been proved recently under a c…
Gibbs Sampler for Matrix Generalized Inverse Gaussian Distributions
Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
Sampling from matrix generalized inverse Gaussian (MGIG) distributions is required in Markov Chain Monte Carlo (MCMC) algorithms for a variety of statistical models. However, an ef…
Spatiotemporal factor models for functional data with application to population map forecast
Tomoya Wakayama, Shonosuke Sugasawa
The proliferation of mobile devices has led to the collection of large amounts of population data. This situation has prompted the need to utilize this rich, multidimensional data…