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This paper provides a user's guide to the general theory of approximate randomization tests developed in Canay, Romano, and Shaikh (2017) when specialized to linear regressions with clustered data. An important feature of the methodology is…

Econometrics · Economics 2022-03-16 Yong Cai , Ivan A. Canay , Deborah Kim , Azeem M. Shaikh

We show how a central limit theorem for Poisson model random polygons implies a central limit theorem for uniform model random polygons. To prove this implication, it suffices to show that in the two models, the variables in question have…

Probability · Mathematics 2012-08-14 John Pardon

We prove a Gaussian process approximation for the sequence of random compositions of a two-color randomly reinforced urn for both the cases with the equal and unequal reinforcement means. By using the Gaussian approximation, the law of the…

Probability · Mathematics 2020-05-08 Li-Xin Zhang

In this paper we show how to extend the Sample-Path Large Deviation Principle for the urn model of Hill, Lane and Sudderth to the case in which the increment of the urn is not a binary variable. In particular, we sketch how to modify the…

Probability · Mathematics 2025-11-19 Simone Franchini

When an experimenter has the option of running an adaptive trial, is it admissible to ignore this option and run a non-adaptive trial instead? We provide a negative answer to this question in the best-arm identification problem, where the…

Machine Learning · Statistics 2025-06-06 Guido Imbens , Chao Qin , Stefan Wager

In this paper, we establish an almost sure central limit theorem for a general random sequence under a strong approximation condition. Additionally, we derive the law of the iterated logarithm for the center of mass corresponding to a…

Probability · Mathematics 2024-07-08 Zhishui Hua , Wei Wanga , Liang Dong

We study a P\'olya-type urn model defined as follows. Start at time 0 with a single ball of some colour. Then, at each time n>0, choose a ball from the urn uniformly at random. With probability 1/2<p<1, return the ball to the urn along with…

Probability · Mathematics 2016-12-01 Erik Thörnblad

The Friedman's urn model is a popular urn model which is widely used in many disciplines. In particular, it is extensively used in treatment allocation schemes in clinical trials. In this paper, we prove that both the urn composition…

Probability · Mathematics 2009-08-30 Li-Xin Zhang , Feifang Hu

In an election in which each voter ranks all of the candidates, we consider the head-to-head results between each pair of candidates and form a labeled directed graph, called the margin graph, which contains the margin of victory of each…

Theoretical Economics · Economics 2020-09-08 Matthew Harrison-Trainor

In this paper, under mild assumptions, we derive a law of large numbers, a central limit theorem with an error estimate, an almost sure invariance principle and a variant of Chernoff bound in finite-state hidden Markov models. These limit…

Information Theory · Computer Science 2012-04-13 Guangyue Han

We prove a Central Limit Theorem for the sequence of random compositions of a two-color randomly reinforced urn. As a consequence, we are able to show that the distribution of the urn limit composition has no point masses.

Probability · Mathematics 2012-11-27 G. Aletti , C. May , P. Secchi

A new approach to adaptive design of clinical trials is proposed in a general multiparameter exponential family setting, based on generalized likelihood ratio statistics and optimal sequential testing theory. These designs are easy to…

Statistics Theory · Mathematics 2011-05-25 Jay Bartroff , Tze Leung Lai

This paper illustrates asymptotic properties for a response-adaptive design generated by a two-color, randomly reinforced urn model. The design considered is optimal in the sense that it assigns patients to the best treatment, with…

Statistics Theory · Mathematics 2009-04-03 Caterina May , Nancy Flournoy

We consider systems of interacting Generalized Friedman's Urns (GFUs) having irreducible mean replacement matrices. The interaction is modeled through the probability to sample the colors from each urn, that is defined as convex combination…

Probability · Mathematics 2018-01-09 Giacomo Aletti , Andrea Ghiglietti

Randomization testing is a fundamental method in statistics, enabling inferential tasks such as testing for (conditional) independence of random variables, constructing confidence intervals in semiparametric location models, and…

Methodology · Statistics 2023-03-21 Yash Nair , Lucas Janson

Performing statistical analyses on collections of graphs is of import to many disciplines, but principled, scalable methods for multi-sample graph inference are few. Here we describe an "omnibus" embedding in which multiple graphs on the…

Methodology · Statistics 2019-06-27 Keith Levin , Avanti Athreya , Minh Tang , Vince Lyzinski , Youngser Park , Carey E. Priebe

The angular bispectrum of spherical random fields has recently gained an enormous importance, especially in connection with statistical inference on cosmological data. In this paper, we provide expressions for its moments of arbitrary order…

Probability · Mathematics 2008-06-05 D. Marinucci

Random spatial networks-that is, graphs whose connectivity is governed by geometric proximity-have emerged as fundamental models for systems constrained by an underlying spatial structure. A prototypical example is the random geometric…

Probability · Mathematics 2026-02-20 Christian Hirsch , Kyeongsik Nam , Moritz Otto

We consider triangular P\'olya urns and show under very weak conditions a general strong limit theorem of the form $X_{ni}/a_{ni}\to \mathcal{X}_i$ a.s., where $X_{ni}$ is the number of balls of colour $i$ after $n$ draws; the constants…

Probability · Mathematics 2024-03-22 Svante Janson

This paper develops an analytic theory for the study of some Polya urns with random rules. The idea is to extend the isomorphism theorem in Flajolet et al. (2006), which connects deterministic balanced urns to a differential system for the…

Combinatorics · Mathematics 2012-07-25 Basile Morcrette , Hosam M. Mahmoud
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