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Organisms and ecological groups accumulate evidence to make decisions. Classic experiments and theoretical studies have explored this process when the correct choice is fixed during each trial. However, we live in a constantly changing…

Neurons and Cognition · Quantitative Biology 2015-10-01 Alan Veliz-Cuba , Zachary P. Kilpatrick , Kresimir Josic

We state and prove a theorem on the partitioning of a randomly selected large population into stationary and non-stationary components by using a property of stationary population identity. Applications of this theorem for practical…

Populations and Evolution · Quantitative Biology 2021-10-20 Arni S. R. Srinivasa Rao

Observation of phenotypic diversity in a population of genetically identical cells is often linked to the stochastic nature of chemical reactions involved in gene regulatory networks. We investigate the distribution of population averaged…

Molecular Networks · Quantitative Biology 2015-06-18 Bhaswati Bhattacharyya , Ziya Kalay

When the underlying probability distribution in a stochastic optimization is observed only through data, various data-driven formulations have been studied to obtain approximate optimal solutions. We show that no such formulations can, in a…

Optimization and Control · Mathematics 2021-05-31 Henry Lam

We consider the extent to which we can learn from a completely randomized experiment whether all individuals have treatment effects that are weakly of the same sign, a condition we call monotonicity. From a classical sampling perspective,…

Econometrics · Economics 2026-01-13 Jiafeng Chen , Jonathan Roth , Jann Spiess

The massive amounts of data that social media generates has facilitated the study of online human behavior on a scale unimaginable a few years ago. At the same time, the much discussed apparent randomness with which people interact online…

Computers and Society · Computer Science 2012-07-23 Chunyan Wang , Bernardo A. Huberman

With recent advances in natural language processing, rationalization becomes an essential self-explaining diagram to disentangle the black box by selecting a subset of input texts to account for the major variation in prediction. Yet,…

Machine Learning · Computer Science 2023-09-12 Wenbo Zhang , Tong Wu , Yunlong Wang , Yong Cai , Hengrui Cai

In this review, we present econometric and statistical methods for analyzing randomized experiments. For basic experiments we stress randomization-based inference as opposed to sampling-based inference. In randomization-based inference,…

Methodology · Statistics 2017-10-26 Susan Athey , Guido Imbens

Can stated preferences inform counterfactual analyses of actual choice? This research proposes a novel approach to researchers who have access to both stated choices in hypothetical scenarios and actual choices, matched or unmatched. The…

Econometrics · Economics 2025-11-18 Romuald Meango , Marc Henry , Ismael Mourifie

This paper develops a method to use singles' data in a non-parametric revealed preference setting of collective household choice. We use it to test the controversial assumption of preference stability between singles and couples, without…

Econometrics · Economics 2026-05-07 Stefan Hubner

In this paper, we make a review on the concepts of rationality across several different fields, namely in economics, psychology and evolutionary biology and behavioural ecology. We review how processes like natural selection can help us…

Artificial Intelligence · Computer Science 2018-12-03 Catarina Moreira

In recent years there has been a spate of papers describing systems for probabilisitic reasoning which do not use numerical probabilities. In some cases the simple set of values used by these systems make it impossible to predict how a…

Artificial Intelligence · Computer Science 2013-02-21 Simon Parsons

Randomized trials are widely considered as the gold standard for evaluating the effects of decision policies. Trial data is, however, drawn from a population which may differ from the intended target population and this raises a problem of…

Methodology · Statistics 2024-10-30 Sofia Ek , Dave Zachariah

Artificial Intelligence (AI) increasingly shows its potential to outperform predicate logic algorithms and human control alike. In automatically deriving a system model, AI algorithms learn relations in data that are not detectable for…

Artificial Intelligence · Computer Science 2022-10-12 Simon Daniel Duque Anton , Daniel Schneider , Hans Dieter Schotten

The random utility model (RUM, McFadden and Richter, 1990) has been the standard tool to describe the behavior of a population of decision makers. RUM assumes that decision makers behave as if they maximize a rational preference over a…

General Economics · Economics 2022-07-05 Victor H. Aguiar , Maria Jose Boccardi , Nail Kashaev , Jeongbin Kim

The finite sensitivity of instruments or detection methods means that data sets in many areas of astronomy, for example cosmological or exoplanet surveys, are necessarily systematically incomplete. Such data sets, where the population being…

Instrumentation and Methods for Astrophysics · Physics 2020-10-14 Adam B. Mantz

We consider the problem of assessing whether, in an individual case, there is a causal relationship between an observed exposure and a response variable. When data are available on similar individuals we may be able to estimate prospective…

Statistics Theory · Mathematics 2023-11-15 Monica Musio , Philip Dawid

In this paper the theory of semi-bounded rationality is proposed as an extension of the theory of bounded rationality. In particular, it is proposed that a decision making process involves two components and these are the correlation…

Artificial Intelligence · Computer Science 2013-05-28 Tshilidzi Marwala

Subjective expected utility theory assumes that decision-makers possess unlimited computational resources to reason about their choices; however, virtually all decisions in everyday life are made under resource constraints - i.e.…

Machine Learning · Statistics 2016-10-07 Pedro A. Ortega , Alan A. Stocker

Advancing our understanding of human behavior hinges on the ability of theories to unveil the mechanisms underlying such behaviors. Measuring the ability of theories and models to predict unobserved behaviors provides a principled method to…

Physics and Society · Physics 2020-04-28 Sergio Cobo-Lopez , Antonia Godoy-Lorite , Jordi Duch , Marta Sales-Pardo , Roger Guimera
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