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09/04/2023
Hierarchical Regression Discontinuity Design: Pursuing Subgroup Treatment Effects
Regression discontinuity design (RDD) is widely adopted for causal infer...
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08/21/2023
An Unbiased Predictor for Skewed Response Variable with Measurement Error in Covariate
We introduce a new small area predictor when the Fay-Herriot normal erro...
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08/11/2023
Clustering and Predicting Multiple Time Series Count Data via Mixture of Bayesian Predictive Syntheses: Analysis of COVID-19 Hospitalisation in Japan and Korea
Since the outbreak of COVID-19, governments and academia have made treme...
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08/03/2023
Similarity-based Random Partition Distribution for Clustering Functional Data
Random partitioned distribution is a powerful tool for model-based clust...
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04/16/2023
Bayesian Causal Synthesis for Supra-Inference on Heterogeneous Treatment Effects
We propose a novel Bayesian methodology to mitigate misspecification and...
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03/01/2023
Posterior Robustness with Milder Conditions: Contamination Models Revisited
Robust Bayesian linear regression is a classical but essential statistic...
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02/20/2023
Gibbs Sampler for Matrix Generalized Inverse Gaussian Distributions
Sampling from matrix generalized inverse Gaussian (MGIG) distributions i...
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02/09/2023
Spatiotemporal factor models for functional data with application to population map forecast
With the proliferation of mobile devices, an increasing amount of popula...
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12/02/2022
Fully Data-driven Normalized and Exponentiated Kernel Density Estimator with Hyvärinen Score
We introduce a new deal of kernel density estimation using an exponentia...
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11/09/2022
Fast and Locally Adaptive Bayesian Quantile Smoothing using Calibrated Variational Approximations
Quantiles are useful characteristics of random variables that can provid...
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08/16/2022
Semiparametric imputation using latent sparse conditional Gaussian mixtures for multivariate mixed outcomes
This paper proposes a flexible Bayesian approach to multiple imputation ...
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08/10/2022
Locally Adaptive Bayesian Isotonic Regression using Half Shrinkage Priors
Isotonic regression or monotone function estimation is a problem of esti...
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07/18/2022
Spatio-temporal smoothing, interpolation and prediction of income distributions based on grouped data
In Japan, the Housing and Land Survey (HLS) provides grouped data on hou...
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04/21/2022
Functional Horseshoe Smoothing for Functional Trend Estimation
Due to developments in instruments and computers, functional observation...
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03/16/2022
Sparse Bayesian Inference on Positive-valued Data using Global-local Shrinkage Priors
In various applications, we deal with high-dimensional positive-valued d...
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03/10/2022
Spatially-Varying Bayesian Predictive Synthesis for Flexible and Interpretable Spatial Prediction
Spatial data are characterized by their spatial dependence, which is oft...
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03/03/2022
On Data Augmentation for Models Involving Reciprocal Gamma Functions
In this paper, we introduce a new and efficient data augmentation approa...
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02/19/2022
Bayesian Quantile Trend Filtering on Graphs using Shrinkage Priors
Quantiles are useful characteristics of random variables that can provid...
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11/01/2021
Spatio-temporal Modeling of Zero-Inflated Count: Efficient Posterior Computation and Application to Monitoring Capelin Distribution in the Barents Sea
We consider a model for predicting the spatio-temporal distribution of a...
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08/26/2021
Robust and Efficient Empirical Bayes Confidence Intervals using γ-Divergence
Although parametric empirical Bayes confidence intervals of multiple nor...
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06/30/2021
Adaptively Robust Geographically Weighted Regression
We develop a new robust geographically weighted regression method in the...
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06/22/2021
On Selection Criteria for the Tuning Parameter in Robust Divergence
While robust divergence such as density power divergence and γ-divergenc...
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06/19/2021
Robust Hierarchical Modeling of Counts under Zero-inflation and Outliers
Count data with zero inflation and large outliers are ubiquitous in many...
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06/13/2021
Adaptation of the Tuning Parameter in General Bayesian Inference with Robust Divergence
We introduce a methodology for robust Bayesian estimation with robust di...
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05/17/2021
General Unbiased Estimating Equations for Variance Components in Linear Mixed Models
This paper introduces a general framework for estimating variance compon...
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04/06/2021
Locally Adaptive Smoothing for Functional Data
Despite increasing accessibility to function data, effective methods for...
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11/03/2020
Spatially Clustered Regression
Spatial regression or geographically weighted regression models have bee...
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06/26/2020
Parametric Bootstrap Confidence Intervals for the Multivariate Fay-Herriot Model
The multivariate Fay-Herriot model is quite effective in combining infor...
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06/11/2020
Grouped GEE Analysis for Longitudinal Data
Generalized estimating equation (GEE) is widely adopted for regression m...
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05/06/2020
Log-Regularly Varying Scale Mixture of Normals for Robust Regression
Linear regression with the classical normality assumption for the error ...
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04/28/2020
Predicting Infection of COVID-19 in Japan: State Space Modeling Approach
The number of confirmed cases of the coronavirus disease (COVID-19) in J...
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04/08/2020
Robust Mixture Modeling using Weighted Complete Estimating Equations
Mixture modeling that takes account of potential heterogeneity in data i...
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03/12/2020
Efficient testing and effect size estimation for set-based genetic association inference via semiparametric multilevel mixture modeling: Application to a genome-wide associatio
In genetic association studies, rare variants with extremely small allel...
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01/23/2020
Shrinkage with Robustness: Log-Adjusted Priors for Sparse Signals
We introduce a new class of distributions named log-adjusted shrinkage p...
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10/02/2019
Robust Bayesian Regression with Synthetic Posterior
Regression models are fundamental tools in statistics, but they typicall...
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09/06/2019
Bayesian Semiparametric Estimation with Nonignorable Nonresponse
Statistical inference with nonresponse is quite challenging, especially ...
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08/19/2019
Bayesian approach to Lorenz curve using time series grouped data
This study is concerned with estimating the inequality measures associat...
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07/02/2019
On Global-local Shrinkage Priors for Count Data
Global-local shrinkage prior has been recognized as useful class of prio...
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06/20/2019
Improving the Accuracy of Confidence Intervals and Regions in Multivariate Random-effects Meta-analysis
Multivariate random-effects meta-analyses have been widely applied in ev...
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06/11/2019
An approximate Bayesian approach to regression estimation with many auxiliary variables
Model-assisted estimation with complex survey data is an important pract...
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05/05/2019
Efficient selection of predictive biomarkers for individual treatment selection
The development of molecular diagnostic tools to achieve individualized ...
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04/25/2019
Estimation and inference for area-wise spatial income distributions from grouped data
Estimating income distributions plays an important role in the measureme...
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04/03/2018
Grouped Heterogeneous Mixture Modeling for Clustered Data
Clustered data which has a grouping structure (e.g. postal area, school,...
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11/17/2017