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stat.ME2025
Complementary strengths of the Neyman-Rubin and graphical causal frameworks
Tetiana Gorbach, Xavier de Luna, Juha Karvanen +1
This article contributes to the discussion on the relationship between the Neyman-Rubin and the graphical frameworks for causal inference. We present specific examples of data-gene…
stat.ME2024
Dynamic programming principle in cost-efficient sequential design: application to switching measurements
Jeongmin Han, Juha Karvanen, Mikko Parviainen
We study sequential cost-efficient design in a situation where each update of covariates involves a fixed time cost typically considerable compared to a single measurement time. Th…