English
Related papers

Related papers: Impossible Inference in Econometrics: Theory and A…

200 papers

Recently, it has been emphasized that the possibility theory framework allows us to distinguish between i) what is possible because it is not ruled out by the available knowledge, and ii) what is possible for sure. This distinction may be…

Artificial Intelligence · Computer Science 2013-01-07 Salem Benferhat , Didier Dubois , Souhila Kaci , Henri Prade

In several decision-making problems, alternatives should be ranked on the basis of paired comparisons between them. We present an axiomatic approach for the universal ranking problem with arbitrary preference intensities, incomplete and…

Computer Science and Game Theory · Computer Science 2019-04-10 László Csató

In many fields of research null hypothesis significance tests and p values are the accepted way of assessing the degree of certainty with which research results can be extrapolated beyond the sample studied. However, there are very serious…

Methodology · Statistics 2020-01-14 Michael Wood

A controversial test for Large Language Models concerns the ability to discern possible from impossible language. While some evidence attests to the models' sensitivity to what crosses the limits of grammatically impossible language, this…

Computation and Language · Computer Science 2025-09-19 Evelina Leivada , Raquel Montero , Paolo Morosi , Natalia Moskvina , Tamara Serrano , Marcel Aguilar , Fritz Guenther

We provide a test for the specification of a structural model without identifying assumptions. We show the equivalence of several natural formulations of correct specification, which we take as our null hypothesis. From a natural empirical…

Econometrics · Economics 2021-02-25 Alfred Galichon , Marc Henry

In Econometrics, imposing restrictions without assuming underlying distributions to modelize complex realities is a valuable methodological tool. However, if a subset of restrictions were not correctly specified, the usual test-statistics…

Methodology · Statistics 2015-10-29 Angel Felipe , Nirian Martín , Pedro Miranda , Leandro Pardo

The incompressibility method is an elementary yet powerful proof technique. It has been used successfully in many areas. To further demonstrate its power and elegance we exhibit new simple proofs using the incompressibility method.

Computational Complexity · Computer Science 2007-05-23 Harry Buhrman , Tao Jiang , Ming Li , Paul Vitanyi

We study finite-sample inference for the trade-off function of two unknown probability distributions, the function that traces the optimal type I/type II error frontier in binary testing. Given samples from distributions $P$ and $Q$, we…

Statistics Theory · Mathematics 2026-05-12 Kaining Shi , Qiaosen Wang , Cong Ma

We introduce the notions of triviality and order-triviality for global invariant types in an arbitrary first-order theory and show that they are well behaved in the NIP context. We show that these two notions agree for invariant global…

Logic · Mathematics 2026-02-24 Slavko Moconja , Predrag Tanović

In applied settings, tests of hypothesis where a nuisance parameter is only identifiable under the alternative often reduces into one of Testing One Hypothesis Multiple times (TOHM). Specifically, a fine discretization of the space of the…

Methodology · Statistics 2022-04-06 Sara Algeri , David A. van Dyk

The incompressibility method is an elementary yet powerful proof technique. It has been used successfully in many areas. To further demonstrate its power and elegance we exhibit new simple proofs using the incompressibility method.

Computational Complexity · Computer Science 2007-05-23 Tao Jiang , Ming Li , Paul Vitanyi

Hypothesis testing in singular statistical models is often regarded as inherently problematic due to non-identifiability and degeneracy of the Fisher information. We show that the fundamental obstruction to testing in such models is not…

Statistics Theory · Mathematics 2026-03-02 Sean Plummer

Two different approaches to dealing with probabilistic knowledge are examined -models and inductive inference. Examples of the first are: influence diagrams [1], Bayesian networks [2], log-linear models [3, 4]. Examples of the second are:…

Artificial Intelligence · Computer Science 2013-04-12 Norman C. Dalkey

In the past decades, weak convergence theory for stochastic processes has become a standard tool for analyzing the asymptotic properties of various statistics. Routinely, weak convergence is considered in the space of bounded functions…

Statistics Theory · Mathematics 2014-08-15 Axel Bücher , Johan Segers , Stanislav Volgushev

Hypothesis tests under order restrictions arise in a wide range of scientific applications. By exploiting inequality constraints, such tests can achieve substantial gains in power and interpretability. However, these gains come at a cost:…

Methodology · Statistics 2026-02-18 Ori Davidov

We review approaches to statistical inference based on randomization. Permutation tests are treated as an important special case. Under a certain group invariance property, referred to as the ``randomization hypothesis,'' randomization…

Econometrics · Economics 2025-02-05 David M. Ritzwoller , Joseph P. Romano , Azeem M. Shaikh

In a recent paper we introduced a much weaker and easy to verify structure than a model category, which we called a "weak fibration category". We further showed that a small weak fibration category can be "completed" into a full model…

Category Theory · Mathematics 2015-07-03 Ilan Barnea , Tomer M. Schlank

Some things are impossible, but some things may be even more impossible than impossible. Levitating a feather using one's mind is impossible in our world, but fits into our intuitive theories of possible worlds, whereas levitating a feather…

Computation and Language · Computer Science 2025-03-03 Jennifer Hu , Felix Sosa , Tomer Ullman

This article extends the hypotheses assessment method to the case with two competing simple hypotheses. In doing so we further clarify the benefits that hypotheses assessments can bring to classical statistical analyses. Given that…

Methodology · Statistics 2025-03-25 Graham N. Bornholt

We give a finite-sample analysis of predictive inference procedures after model selection in regression with random design. The analysis is focused on a statistically challenging scenario where the number of potentially important…

Statistics Theory · Mathematics 2009-08-26 Hannes Leeb