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We consider goodness-of-fit tests for the distribution of the composed error in Stochastic Frontier Models. The proposed test statistic utilizes the characteristic function of the composed error term, and is formulated as a weighted…

Statistics Theory · Mathematics 2022-03-01 Simos G. Meintanis , Christos K. Papadimitriou

This paper studies choice situations in which a decision maker can choose multiple alternatives. Given a menu of available options, the decision maker selects a subset of the menu with certain probabilities. We employ an axiomatic approach…

Theoretical Economics · Economics 2025-11-25 Tri Phu Vu

Our study focuses on fractional order compartment models derived from underlying physical stochastic processes, providing a more physically grounded approach compared to models that use the dynamical system approach by simply replacing…

Context: The importance of the feature modeling for the software product lines considering the modeling and management of the variability. Objective: Define a protocol to conduct a systematic mapping study to summarize and synthesize the…

Software Engineering · Computer Science 2021-03-31 Samuel Sepúlveda , Marcelo Esperguel

Inverse optimal control can be used to characterize behavior in sequential decision-making tasks. Most existing work, however, is limited to fully observable or linear systems, or requires the action signals to be known. Here, we introduce…

Machine Learning · Computer Science 2023-10-31 Dominik Straub , Matthias Schultheis , Heinz Koeppl , Constantin A. Rothkopf

Determining an individual's strategic reasoning capability based solely on choice data is a complex task. This complexity arises because sophisticated players might have non-equilibrium beliefs about others, leading to non-equilibrium…

General Economics · Economics 2026-02-04 Wei James Chen , Meng-Jhang Fong , Po-Hsuan Lin

Stochastic orders are very useful tool to compare the lifetimes of two coherent systems. We show that, under certain conditions, a coherent system of used components performs better (worse) than a used coherent system with respect to…

Applications · Statistics 2016-01-20 Nil Kamal Hazra , Asok K. Nanda

In performative prediction, the choice of a model influences the distribution of future data, typically through actions taken based on the model's predictions. We initiate the study of stochastic optimization for performative prediction.…

Machine Learning · Computer Science 2021-02-22 Celestine Mendler-Dünner , Juan C. Perdomo , Tijana Zrnic , Moritz Hardt

In this paper, we study planning in stochastic systems, modeled as Markov decision processes (MDPs), with preferences over temporally extended goals. Prior work on temporal planning with preferences assumes that the user preferences form a…

Robotics · Computer Science 2023-03-09 Hazhar Rahmani , Abhishek N. Kulkarni , Jie Fu

Comparisons of different treatments or production processes are the goals of a significant fraction of applied research. Unsurprisingly, two-sample problems play a main role in Statistics through natural questions such as `Is the the new…

Methodology · Statistics 2017-09-05 P. C. Álvarez-Esteban , E. del Barrio , J. A. Cuesta-Albertos , C. Matrán

How can we discern whether the covariance operator of a stochastic process is of reduced rank, and if so, what its precise rank is? And how can we do so at a given level of confidence? This question is central to a great deal of methods for…

Methodology · Statistics 2020-08-11 Anirvan Chakraborty , Victor M. Panaretos

The partial monitoring (PM) framework provides a theoretical formulation of sequential learning problems with incomplete feedback. On each round, a learning agent plays an action while the environment simultaneously chooses an outcome. The…

Machine Learning · Computer Science 2024-05-17 Maxime Heuillet , Ola Ahmad , Audrey Durand

This paper studies whether rationality can be computed. Rationality is defined as the use of complete information, which is processed with a perfect biological or physical brain, in an optimized fashion. To compute rationality one needs to…

Artificial Intelligence · Computer Science 2018-12-27 Tshilidzi Marwala

Computer systems can be found everywhere: in space, in our homes, in our cars, in our pockets, and sometimes even in our own bodies. For concerns of safety, economy, and convenience, it is important that such systems work correctly.…

Logic in Computer Science · Computer Science 2019-05-22 Mathias Ruggaard Pedersen

The standard rational choice model describes individuals as making choices by selecting the best option from a menu. A wealth of evidence instead suggests that individuals often filter menus into smaller sets - consideration sets - from…

Theoretical Economics · Economics 2023-01-16 Tonna Emenuga

In the application of machine learning to real-life decision-making systems, e.g., credit scoring and criminal justice, the prediction outcomes might discriminate against people with sensitive attributes, leading to unfairness. The commonly…

Machine Learning · Computer Science 2022-03-21 Suyun Liu , Luis Nunes Vicente

We present a method for incorporating a stochastic point of view into physics exercises of mathematics education. The core of our method is the randomization of some inputs, the system model used does not differ from what we would use in…

Physics Education · Physics 2025-09-16 Matyas Barczy , Imre Kocsis , Csaba Gábor Kézi

Ranking and scoring are ubiquitous. We consider the setting in which an institution, called a ranker, evaluates a set of individuals based on demographic, behavioral or other characteristics. The final output is a ranking that represents…

Databases · Computer Science 2016-10-28 Ke Yang , Julia Stoyanovich

We present a formal language for specifying qualitative preferences over temporal goals and a preference-based planning method in stochastic systems. Using automata-theoretic modeling, the proposed specification allows us to express…

Artificial Intelligence · Computer Science 2021-03-29 Jie Fu

We consider the conditional randomization test as a way to account for covariate imbalance in randomized experiments. The test accounts for covariate imbalance by comparing the observed test statistic to the null distribution of the test…

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