21 citations · 90 across the 97 of their papers we have counts for
8 papers · 1 filter
Spatially Clustered Regression
Shonosuke Sugasawa, Daisuke Murakami
Spatial regression or geographically weighted regression models have been widely adopted to capture the effects of auxiliary information on a response variable of interest over a r…
Parametric Bootstrap Confidence Intervals for the Multivariate Fay-Herriot Model
Takumi Saegusa, Shonosuke Sugasawa, Partha Lahiri
The multivariate Fay-Herriot model is quite effective in combining information through correlations among small area survey estimates of related variables or historical survey esti…
Grouped Generalized Estimating Equations for Longitudinal Data Analysis
Tsubasa Ito, Shonosuke Sugasawa
Generalized estimating equation (GEE) is widely adopted for regression modeling for longitudinal data, taking account of potential correlations within the same subjects. Although t…
Log-Regularly Varying Scale Mixture of Normals for Robust Regression
Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
Linear regression with the classical normality assumption for the error distribution may lead to an undesirable posterior inference of regression coefficients due to the potential…
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…
Efficient testing and effect size estimation for set-based genetic association inference via semiparametric multilevel mixture modeling: Application to a genome-wide association study of coronary artery disease
Shonosuke Sugasawa, Hisashi Noma
In genetic association studies, rare variants with extremely small allele frequency play a crucial role in complex traits, and the set-based testing methods that jointly assess the…
Shrinkage with Robustness: Log-Adjusted Priors for Sparse Signals
Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
We introduce a new class of distributions named log-adjusted shrinkage priors for the analysis of sparse signals, which extends the three parameter beta priors by multiplying an ad…