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20152025
most citedSmall area estimation of general finite-population parameters based on grouped data

4 citations · 4 across the 10 of their papers we have counts for

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8 papers · 1 filter

stat.ME2024

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,…

stat.ME2019

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…

stat.ME2019

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…

stat.ME2019★ 4 cited

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…

stat.ME2017

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…

stat.ME2015

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…

stat.ME2015

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…

stat.ME2015

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…