21 citations · 40 across the 63 of their papers we have counts for
8 papers · 1 filter
Dynamic Spatio-temporal Zero-inflated Poisson Models for Predicting Capelin Distribution in the Barents Sea
Shonosuke Sugasawa, Tomoyuki Nakagawa, Hiroko Kato Solvang +2
We consider modeling and prediction of Capelin distribution in the Barents sea based on zero-inflated count observation data that vary continuously over a specified survey region.…
Adaptively Robust Small Area Estimation: Balancing Robustness and Efficiency of Empirical Bayes Confidence Intervals
Daisuke Kurisu, Takuya Ishihara, Shonosuke Sugasawa
Empirical Bayes small area estimation based on the well-known Fay-Herriot model may produce unreliable estimates when outlying areas exist. Existing robust methods against outliers…
On Selection Criteria for the Tuning Parameter in Robust Divergence
Shonosuke Sugasawa, Shouto Yonekura
While robust divergence such as density power divergence and -divergence is helpful for robust statistical inference in the presence of outliers, the tuning parameter that contr…
Adaptively Robust Geographically Weighted Regression
Shonosuke Sugasawa, Daisuke Murakami
We develop a new robust geographically weighted regression method in the presence of outliers. We embed the standard geographically weighted regression in robust objective function…
Robust Bayesian Modeling of Counts with Zero inflation and Outliers: Theoretical Robustness and Efficient Computation
Yasuyuki Hamura, Kaoru Irie, Shonosuke Sugasawa
Count data with zero inflation and large outliers are ubiquitous in many scientific applications. However, posterior analysis under a standard statistical model, such as Poisson or…
Adaptation of the Tuning Parameter in General Bayesian Inference with Robust Divergence
Shouto Yonekura, Shonosuke Sugasawa
We introduce a methodology for robust Bayesian estimation with robust divergence (e.g., density power divergence or γ-divergence), indexed by a single tuning parameter. It is well…