13 citations · 20 across the 15 of their papers we have counts for
16 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…
General Bayesian quantile regression for counts via generative modeling
Yuta Yamauchi, Genya Kobayashi, Shonosuke Sugasawa
Count data frequently arises in biomedical applications, such as the length of hospital stay. However, their discrete nature poses significant challenges for appropriately modeling…
Bayesian Benchmarking Small Area Estimation via Entropic Tilting
Shonosuke Sugasawa, Genya Kobayashi, Yuki Kawakubo
Benchmarking estimation and its risk evaluation is a practically important issue in small area estimation. While Bayesian methods have been widely adopted in small area estimation,…
Bayesian factor zero-inflated Poisson model for multiple grouped count data
Genya Kobayashi, Yuta Yamauchi
This paper proposes a computationally efficient Bayesian factor model for multiple grouped count data. Adopting the link function approach, the proposed model can capture the assoc…
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…
Spatio-temporal smoothing, interpolation and prediction of income distributions based on grouped data
Genya Kobayashi, Shonosuke Sugasawa, Yuki Kawakubo
The Housing and Land Survey (HLS) of Japan provides municipality-level grouped data on household incomes. Although such data can be invaluable for effective local policymaking, the…
Predicting Infection of COVID-19 in Japan: State Space Modeling Approach
Genya Kobayashi, Shonosuke Sugasawa, Hiromasa Tamae +1
The number of confirmed cases of the coronavirus disease (COVID-19) in Japan has been increasing day by day and has had a serious impact on the society especially after the declara…
Robust Fitting of Mixture Models using Weighted Complete Estimating Equations
Shonosuke Sugasawa, Genya Kobayashi
Mixture modeling, which considers the potential heterogeneity in data, is widely adopted for classification and clustering problems. Mixture models can be estimated using the Expec…
Bayesian approach to Lorenz curve using time series grouped data
Genya Kobayashi, Yuta Yamauchi, Kazuhiko Kakamu +2
This study is concerned with estimating the inequality measures associated with the underlying hypothetical income distribution from the times series grouped data on the Lorenz cur…
Estimation and inference for area-wise spatial income distributions from grouped data
Shonosuke Sugasawa, Genya Kobayashi, Yuki Kawakubo
Estimating income distributions plays an important role in the measurement of inequality and poverty over space. The existing literature on income distributions predominantly focus…
Small area estimation of general finite-population parameters based on grouped data
Yuki Kawakubo, Genya Kobayashi
This paper proposes a new model-based approach to small area estimation of general finite-population parameters based on grouped data or frequency data, which is often available fr…
Latent Mixture Modeling for Clustered Data
Shonosuke Sugasawa, Genya Kobayashi, Yuki Kawakubo
This article proposes a mixture modeling approach to estimating cluster-wise conditional distributions in clustered (grouped) data. We adapt the mixture-of-experts model to the lat…
Bayesian Nonparametric Instrumental Variable Regression Approach to Quantile Inference
Genya Kobayashi, Kota Ogasawara
This study extends the Bayesian nonparametric instrumental variable regression model to determine the structural effects of covariates on the conditional quantile of the response v…
Approximate Bayesian Computation for Lorenz Curves from Grouped Data
Genya Kobayashi, Kazuhiko Kakamu
This paper proposes a new Bayesian approach to estimate the Gini coefficient from the Lorenz curve based on grouped data. The proposed approach assumes a hypothetical income distri…
Bayesian Endogenous Tobit Quantile Regression
Genya Kobayashi
This study proposes -th Tobit quantile regression models with endogenous variables. In the first stage regression of the endogenous variable on the exogenous variables, the assu…