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We propose a sound and complete proof rule ProbTA for quantitative analysis of violation probability of probabilistic programs. Our approach extends the technique of trace abstraction with probability in the control-flow randomness style,…

Programming Languages · Computer Science 2022-03-10 Guanyan Li , Zhilei Han , Fei He

Given a random walk a method is presented to produce a matrix of transition probabilities that is consistent with that random walk. The method is a kind of reverse application of the usual ergodicity and is tested by using a transition…

General Physics · Physics 2017-08-02 Lawrence S. Schulman

By using straightforward frequency arguments we classify transformations of probabilities which can be generated by transition from one preparation procedure (context) to another. There are three classes of transformations corresponding to…

Quantum Physics · Physics 2009-11-07 Andrei Khrennikov

We define an extension of lambda-calculus with dependents types that enables us to encode transparent and opaque probabilistic programs and prove a strong normalisation result for it by a reducibility technique. While transparent…

Logic in Computer Science · Computer Science 2026-03-10 Francesco A. Genco

The emergent field of probabilistic numerics has thus far lacked clear statistical principals. This paper establishes Bayesian probabilistic numerical methods as those which can be cast as solutions to certain inverse problems within the…

Methodology · Statistics 2019-11-15 Jon Cockayne , Chris Oates , Tim Sullivan , Mark Girolami

We introduce a family of maps generating continued fractions where the digit $1$ in the numerator is replaced cyclically by some given non-negative integers $(N_1,\ldots,N_m)$. We prove the convergence of the given algorithm, and study the…

Dynamical Systems · Mathematics 2021-12-09 Karma Dajani , Niels Langeveld

Building on recent results regarding symmetric probabilistic constructions of countable structures, we provide a method for constructing probability measures, concentrated on certain classes of countably infinite structures, that are…

Logic · Mathematics 2015-11-24 Nathanael Ackerman , Cameron Freer , Jaroslav Nesetril , Rehana Patel

We study the termination problem for probabilistic term rewrite systems. We prove that the interpretation method is sound and complete for a strengthening of positive almost sure termination, when abstract reduction systems and term rewrite…

Symbolic Computation · Computer Science 2018-02-28 Martin Avanzini , Ugo Dal Lago , Akihisa Yamada

A notion of probabilistic lambda-calculus usually comes with a prescribed reduction strategy, typically call-by-name or call-by-value, as the calculus is non-confluent and these strategies yield different results. This is a break with one…

Logic in Computer Science · Computer Science 2020-02-21 Ugo Dal Lago , Giulio Guerrieri , Willem Heijltjes

To support the understanding of declarative probabilistic programming languages, we introduce a lambda-calculus with a fair binary probabilistic choice that chooses between its arguments with equal probability. The reduction strategy of the…

Logic in Computer Science · Computer Science 2022-05-31 David Sabel , Manfred Schmidt-Schauß , Luca Maio

The linear-algebraic lambda-calculus and the algebraic lambda-calculus are untyped lambda-calculi extended with arbitrary linear combinations of terms. The former presents the axioms of linear algebra in the form of a rewrite system, while…

Logic in Computer Science · Computer Science 2012-03-29 Pablo Buiras , Alejandro Díaz-Caro , Mauro Jaskelioff

In this note, we consider a class of composition operators on Lebesgue spaces with variable exponents over metric measure spaces. Taking advantage of the compatibility between the metric-measurable structure and the regularity properties of…

Functional Analysis · Mathematics 2025-02-04 Javier Henríquez-Amador , Carlos F. Álvarez

Nonprobability (convenience) samples are increasingly sought to reduce the estimation variance for one or more population variables of interest that are estimated using a randomized survey (reference) sample by increasing the effective…

Probabilistic automata (PA), also known as probabilistic nondeterministic labelled transition systems, combine probability and nondeterminism. They can be given different semantics, like strong bisimilarity, convex bisimilarity, or (more…

Logic in Computer Science · Computer Science 2023-06-22 Filippo Bonchi , Alexandra Silva , Ana Sokolova

The extensive deployment of probabilistic algorithms has radically changed our perspective on several well-established computational notions. Correctness is probably the most basic one. While a typical probabilistic program cannot be said…

Logic in Computer Science · Computer Science 2025-02-17 Francesco A. Genco , Giuseppe Primiero

We introduce a new method, combination of random testing and abstract interpretation, for the analysis of programs featuring both probabilistic and non-probabilistic nondeterminism. After introducing "ordinary" testing, we show how to…

Programming Languages · Computer Science 2007-05-23 David Monniaux

We consider impulsive dynamical systems defined on compact metric spaces and their respective impulsive semiflows. We establish sufficient conditions for the existence of probability measures which are invariant by such impulsive semiflows.…

Dynamical Systems · Mathematics 2015-06-19 Jose F. Alves , Maria Carvalho

Suppose $a_n$ is a real, nonnegative sequence that does not increase exponentially. For any $p<1$ we contruct a Lebesgue measurable set $E \subseteq \mathbb{R}$ which has measure at least $p$ in any unit interval and which contains no…

Classical Analysis and ODEs · Mathematics 2024-12-18 Mihail N. Kolountzakis , Effie Papageorgiou

We study invariant measures for random countable (finite or infinite) conformal iterated function systems (IFS) with arbitrary overlaps. We do not assume any type of separation condition. We prove, under a mild assumption of finite entropy,…

Dynamical Systems · Mathematics 2015-03-24 Eugen Mihailescu , Mariusz Urbanski

A composite likelihood is a non-genuine likelihood function that allows to make inference on limited aspects of a model, such as marginal or conditional distributions. Composite likelihoods are not proper likelihoods and need therefore…

Methodology · Statistics 2021-04-06 Michele Lambardi di San Miniato , Nicola Sartori