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Related papers: Are Synthetic Control Weights Balancing Score?

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A/B tests, also known as randomized controlled experiments (RCTs), are the gold standard for evaluating the impact of new policies, products, or decisions. However, these tests can be costly in terms of time and resources, potentially…

Machine Learning · Statistics 2025-01-03 Shima Nassiri , Mohsen Bayati , Joe Cooprider

Symmetry properties of the evolution equation and the state to be controlled are shown to determine the basic features of the linear control of unstable orbits. In particular, the selection of control parameters and their minimal number are…

chao-dyn · Physics 2009-10-30 R. O. Grigoriev , M. C. Cross

We study the effect of extrinsic noise in metabolic networks. We introduce external random fluctuations at the kinetic level, and show how these lead to a stochastic generalization of standard Metabolic Control Analysis. While Summation and…

Subcellular Processes · Quantitative Biology 2015-05-13 Andrea Rocco

Controlled experiments are widely used in many applications to investigate the causal relationship between input factors and experimental outcomes. A completely randomized design is usually used to randomly assign treatment levels to…

Methodology · Statistics 2026-05-12 Yiou Li , Lulu Kang , Xiao Huang

Robust control theory studies the effect of noise, disturbances, and other uncertainty on system performance. Despite growing recognition across science and engineering that robustness and efficiency tradeoffs dominate the evolution and…

Optimization and Control · Mathematics 2016-06-14 Yoke Peng Leong , John C. Doyle

We introduce a new test for conditional independence which is based on what we call the weighted generalised covariance measure (WGCM). It is an extension of the recently introduced generalised covariance measure (GCM). To test the null…

Methodology · Statistics 2022-05-17 Cyrill Scheidegger , Julia Hörrmann , Peter Bühlmann

This paper investigates a class of controlled stochastic partial differential equations (SPDEs) arising in the modeling of composite materials with spatially varying properties. The state equation describes the evolution of a material…

Optimization and Control · Mathematics 2025-02-24 Nacira Agram , Isabelle Turpin , Eya Zougar

Social scientists often study how a policy reform impacted a single targeted country. Increasingly, this is done with the synthetic control method (SCM). SCM models the country's counterfactual (non-reform or untreated) trajectory as a…

Applications · Statistics 2019-10-15 Elias Tuomaala

The synthetic control method has become a widely popular tool to estimate causal effects with observational data. Despite this, inference for synthetic control methods remains challenging. Often, inferential results rely on linear factor…

Methodology · Statistics 2024-07-09 Ignacio Martinez , Jaume Vives-i-Bastida

Tests for paired censored outcomes have been extensively studied, with some justified in the context of randomization-based inference. These tests are primarily designed to detect an overall treatment effect across the entire follow-up…

Methodology · Statistics 2025-06-10 Sangjin Lee , Kwonsang Lee

The self-consistent cranking method is tested by comparing the cranking calculations in the interacting boson model with the exact results obtained from the SU(3) and O(6) dynamical symmetries and from numerical diagonalization. The method…

Nuclear Theory · Physics 2009-10-31 Serdar Kuyucak , Michiaki Sugita

The synthetic control method (SCM) is widely used for constructing the counterfactual of a treated unit based on data from control units in a donor pool. Allowing the donor pool contains more control units than time periods, we propose a…

Econometrics · Economics 2026-05-19 Chengwang Liao , Zhentao Shi , Yapeng Zheng

The paper describes a novel method of sampled-data in space (spatial variable) control of scalar semilinear systems of parabolic and hyperbolic type with unknown parameters and distributed disturbances. A finite set of sampled-data in the…

Systems and Control · Electrical Eng. & Systems 2020-09-30 Igor Furtat , Pavel Gushchin

Symbolic approaches to the control design over complex systems employ the construction of finite-state models that are related to the original control systems, then use techniques from finite-state synthesis to compute controllers…

Optimization and Control · Mathematics 2013-02-18 Majid Zamani , Peyman Mohajerin Esfahani , Rupak Majumdar , Alessandro Abate , John Lygeros

A new class of control problems is discussed - homeostasis control. Homeostasis control problems can be considered as control problems with a given target set, in particular, as a problem of stabilizing the values of some target function,…

Optimization and Control · Mathematics 2023-11-28 Alexander Fradkov

Obesity is a chronic disease that can lead to an increased risk of other serious chronic diseases and even death. We present switching and time-delayed feedback-based model free control methods for the dynamic management of body mass and…

Systems and Control · Computer Science 2017-04-05 Mahmood Karimi , Ramesh R. Rao

In a clustered observational study, a treatment is assigned to groups and all units within the group are exposed to the treatment. We develop a new method for statistical adjustment in clustered observational studies using approximate…

Methodology · Statistics 2023-03-06 Luke Keele , Eli Ben-Michael , Lindsay Page

Game balancing is an important part of the (computer) game design process, in which designers adapt a game prototype so that the resulting gameplay is as entertaining as possible. In industry, the evaluation of a game is often based on…

Human-Computer Interaction · Computer Science 2016-03-15 Vanessa Volz , Günter Rudolph , Boris Naujoks

In observational studies, weighting methods that directly optimize the balance between treatment and covariates have received much attention lately; however these have mainly focused on binary treatments. Inspired by domain adaptation, we…

Statistics Theory · Mathematics 2020-02-27 Guillaume Martinet

Conformal risk control (CRC) provides distribution-free guarantees for controlling the expected loss at a user-specified level. Existing theory typically assumes that the loss decreases monotonically with a tuning parameter that governs the…

Machine Learning · Statistics 2026-04-21 Tareq Aldirawi , Yun Li , Wenge Guo