117 citations · 191 across the 25 of their papers we have counts for
6 papers · 1 filter
Fast boundary-aware spatial intensity estimation on complex domains
Takumi Nakagawa, Kōsaku Takanashi, Kenichiro McAlinn +1
Spatial intensity maps are routinely used to summarize point patterns on geographically constrained regions, such as islands, coastlines, watersheds, ecological reserves, and admin…
FlowSDR: Sufficient Dimension Reduction via Conditional Normalizing Flows
Yuexiao Dong, Kenichiro Mcalinn, Edoardo Airoldi +1
Sufficient dimension reduction (SDR) seeks a low-dimensional linear projection of predictors that preserves the conditional distribution of the response. Existing methods target th…
An Entropy-Energy Identity for Predictive Kullback-Leibler Regret in Infinitely Divisible Location Models
Kōsaku Takanashi, Kenichiro McAlinn
We consider predictive density estimation under logarithmic score for -dimensional infinitely divisible location models. Taking the formal Bayes predictive density under the Leb…
Predictive Synthesis under Sporadic Participation: Evidence from Inflation Density Surveys
Matthew C. Johnson, Matteo Luciani, Minzhengxiong Zhang +1
Central banks rely on density forecasts from professional surveys to assess inflation risks and communicate uncertainty. A central challenge in using these surveys is irregular par…
When Is Generalized Bayes Bayesian? A Decision-Theoretic Characterization of Loss-Based Updating
Kenichiro McAlinn, Kōsaku Takanashi
Loss-based updating, including generalized Bayes, Gibbs, and quasi-posteriors, replaces likelihoods by a user-chosen loss and produces a posterior-like distribution via exponential…
Dynamic causal inference with time series data
Tanique Schaffe-Odeleye, Kōsaku Takanashi, Vishesh Karwa +2
We generalize the potential outcome framework to time series with an intervention by defining causal effects on stochastic processes. Interventions in dynamic systems alter not onl…