4 citations · 4 across the 10 of their papers we have counts for
11 papers
Multilevel Decomposition of Generalized Entropy Measures Using Constrained Bayes Estimation: An Application to Japanese Regional Data
Yuki Kawakubo, Kazuhiko Kakamu
We propose a method for multilevel decomposition of generalized entropy (GE) measures that explicitly accounts for nested population structures such as national, regional, and subr…
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,…
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…
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…
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…
Small Area Estimation with Spatially Varying Natural Exponential Families
Shonosuke Sugasawa, Yuki Kawakubo, Kota Ogasawara
Two-stage hierarchical models have been widely used in small area estimation to produce indirect estimates of areal means. When the areas are treated exchangeably and the model par…
A Variant of AIC based on the Bayesian Marginal Likelihood
Yuki Kawakubo, Tatsuya Kubokawa, Muni S. Srivastava
We propose information criteria that measure the prediction risk of a predictive density based on the Bayesian marginal likelihood from a frequentist point of view. We derive crite…
Conditional Akaike information under covariate shift with application to small area estimation
Yuki Kawakubo, Shonosuke Sugasawa, Tatsuya Kubokawa
In this study, we consider the problem of selecting explanatory variables of fixed effects in linear mixed models under covariate shift, which is when the values of covariates in t…