Hiroshi Yadohisa

Hiroshi Yadohisa

Doshisha University

H-index: 12

Asia-Japan

About Hiroshi Yadohisa

Hiroshi Yadohisa, With an exceptional h-index of 12 and a recent h-index of 7 (since 2020), a distinguished researcher at Doshisha University, specializes in the field of Statistics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Quantile Outcome Adaptive Lasso: Covariate Selection for Inverse Probability Weighting Estimator of Quantile Treatment Effects

Analysis of Contingency Table by Two-Mode Two-Way Multidimensional Scaling with Bayesian Estimation

Causal rule ensemble method for estimating heterogeneous treatment effect with consideration of prognostic effects

Canonical Dependency Analysis Using a Bias-Corrected Statistics Matrix

Bayesian Geographically Weighted Regression using Fused Lasso Prior

Clustered Sparse Structural Equation Modeling for Heterogeneous Data

Data Augmentation Using Pretrained Models in Japanese Grammatical Error Correction

Estimation and visualization of heterogeneous treatment effects for multiple outcomes

Hiroshi Yadohisa Information

University

Position

___

Citations(all)

521

Citations(since 2020)

202

Cited By

369

hIndex(all)

12

hIndex(since 2020)

7

i10Index(all)

14

i10Index(since 2020)

5

Email

University Profile Page

Doshisha University

Google Scholar

View Google Scholar Profile

Hiroshi Yadohisa Skills & Research Interests

Statistics

Top articles of Hiroshi Yadohisa

Title

Journal

Author(s)

Publication Date

Quantile Outcome Adaptive Lasso: Covariate Selection for Inverse Probability Weighting Estimator of Quantile Treatment Effects

arXiv preprint arXiv:2402.18185

Takehiro Shoji

Jun Tsuchida

Hiroshi Yadohisa

2024/2/28

Analysis of Contingency Table by Two-Mode Two-Way Multidimensional Scaling with Bayesian Estimation

Jun Tsuchida

Hiroshi Yadohisa

2024/1/26

Causal rule ensemble method for estimating heterogeneous treatment effect with consideration of prognostic effects

arXiv preprint arXiv:2307.14766

Mayu Hiraishi

Ke Wan

Kensuke Tanioka

Hiroshi Yadohisa

Toshio Shimokawa

2023/7/27

Canonical Dependency Analysis Using a Bias-Corrected Statistics Matrix

Journal of Statistical Theory and Practice

Jun Tsuchida

Hiroshi Yadohisa

2024/3

Bayesian Geographically Weighted Regression using Fused Lasso Prior

arXiv preprint arXiv:2402.18186

Toshiki Sakai

Jun Tsuchida

Hiroshi Yadohisa

2024/2/28

Clustered Sparse Structural Equation Modeling for Heterogeneous Data

Journal of Classification

Ippei Takasawa

Kensuke Tanioka

Hiroshi Yadohisa

2023/11

Data Augmentation Using Pretrained Models in Japanese Grammatical Error Correction

Transactions of the Japanese Society for Artificial Intelligence

Hideyoshi Kato

Masaaki Okabe

Michiharu Kitano

Hiroshi Yadohisa

2023/7

Estimation and visualization of heterogeneous treatment effects for multiple outcomes

Statistics in Medicine

Shintaro Yuki

Kensuke Tanioka

Hiroshi Yadohisa

2023/2/28

Tucker-3 decomposition with sparse core array using a penalty function based on Gini-index

Japanese Journal of Statistics and Data Science

Jun Tsuchida

Hiroshi Yadohisa

2022/12

Wilcoxon-type Multivariate Cluster Elastic Net

arXiv preprint arXiv:2209.13354

Mayu Hiraishi

Kensuke Tanioka

Hiroshi Yadohisa

2022/9/27

F-measure maximizing logistic regression

Communications in Statistics-Simulation and Computation

Masaaki Okabe

Jun Tsuchida

Hiroshi Yadohisa

2022/5/25

Clustering for time-varying relational count data

Computational statistics & data analysis

Satoshi Goto

Mariko Takagishi

Hiroshi Yadohisa

2021/4/1

K-means generalized maximum entropy estimation for structural equation modeling: An information theoretic-based model

Behaviormetrika

Thi Binh An Duong

Jun Tsuchida

Hiroshi Yadohisa

2021/1

Estimation and visualization of treatment effects for multiple outcomes

arXiv preprint arXiv:2108.00163

Shintaro Yuki

Kensuke Tanioka

Hiroshi Yadohisa

2021/7/31

Estimation of causal effect using propensity score and weighted-average method

Procedia Computer Science

Ryo Otani

Hiroshi Yadohisa

2020/1/1

An estimation of causal structure based on Latent LiNGAM for mixed data

Behaviormetrika

Mako Yamayoshi

Jun Tsuchida

Hiroshi Yadohisa

2020/1

Revealing changes in brain functional networks caused by focused-attention meditation using Tucker3 clustering

Frontiers in Human Neuroscience

Takuma Miyoshi

Kensuke Tanioka

Shoko Yamamoto

Hiroshi Yadohisa

Tomoyuki Hiroyasu

...

2020/1/22

See List of Professors in Hiroshi Yadohisa University(Doshisha University)