experimental design 1local projection 1markov switchback 1policy evaluation 1risk calibration 1time series 1
From the 1 of 3 linked papers with an AI index.
3 papers
stat.ME2026
Calibrated Horizon-Weighted Local Projection Designs for Markov Switchbacks
Makoto Nakakita, Teruo Nakatsuma
The paper develops a calibrated design method for Markov switchback experiments that selects persistence levels to minimize various risk measures for dynamic local‑projection targe…
stat.ME2025
Convergence Rate of Efficient MCMC with Ancillarity-Sufficiency Interweaving Strategy for Panel Data Models
Makoto Nakakita, Tomoki Toyabe, Teruo Nakatsuma +1
Improving Markov chain Monte Carlo algorithm efficiency is essential for enhancing computational speed and inferential accuracy in Bayesian analysis. These improvements can be effe…
cs.CL2024
Do GPT Language Models Suffer From Split Personality Disorder? The Advent Of Substrate-Free Psychometrics
Peter Romero, Stephen Fitz, Teruo Nakatsuma
Previous research on emergence in large language models shows these display apparent human-like abilities and psychological latent traits. However, results are partly contradicting…