4 papers · 1 filter
Doubly Robust Criterion for Causal Inference
Takamichi Baba, Yoshiyuki Ninomiya
The semiparametric estimation approach, which includes inverse-probability-weighted and doubly robust estimation using propensity scores, is a standard tool in causal inference, an…
Prior Intensified Information Criterion
Yoshiyuki Ninomiya
The widely applicable information criterion (WAIC) has been used as a model selection criterion for Bayesian statistics in recent years. It is an asymptotically unbiased estimator…
Selective Inference in Propensity Score Analysis
Yoshiyuki Ninomiya, Yuta Umezu, Ichiro Takeuchi
Selective inference (post-selection inference) is a methodology that has attracted much attention in recent years in the fields of statistics and machine learning. Naive inference…
Smoothly varying ridge regularization
Daeju Kim, Shuichi Kawano, Yoshiyuki Ninomiya
A basis expansion with regularization methods is much appealing to the flexible or robust nonlinear regression models for data with complex structures. When the underlying function…