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Related papers: Testing of sequences by simulation

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Let $(X_i)_{i=1,...,n}$ be a possibly nonstationary sequence such that $\mathscr{L}(X_i)=P_n$ if $i\leq n\theta$ and $\mathscr{L}(X_i)=Q_n$ if $i>n\theta$, where $0<\theta <1$ is the location of the change-point to be estimated. We…

Statistics Theory · Mathematics 2009-09-29 Samir Ben Hariz , Jonathan J. Wylie , Qiang Zhang

We study sorting of permutations by random swaps if each comparison gives the wrong result with some fixed probability $p<1/2$. We use this process as prototype for the behaviour of randomized, comparison-based optimization heuristics in…

Neural and Evolutionary Computing · Computer Science 2018-03-14 Tomáš Gavenčiak , Barbara Geissmann , Johannes Lengler

Complex phenomena in engineering and the sciences are often modeled with computationally intensive feed-forward simulations for which a tractable analytic likelihood does not exist. In these cases, it is sometimes necessary to estimate an…

Methodology · Statistics 2020-06-18 Niccolò Dalmasso , Ann B. Lee , Rafael Izbicki , Taylor Pospisil , Ilmun Kim , Chieh-An Lin

A computer simulation, such as a genetic algorithm, that uses IEEE standard floating-point arithmetic may not produce exactly the same results in two different runs, even if it is rerun on the same computer with the same input and random…

Adaptation and Self-Organizing Systems · Physics 2007-05-23 Theodore C. Belding

Let $(Y,X_1,...,X_m)$ be a random vector. It is desired to predict $Y$ based on $(X_1,...,X_m)$. Examples of prediction methods are regression, classification using logistic regression or separating hyperplanes, and so on. We consider the…

Statistics Theory · Mathematics 2007-06-13 Eitan Greenshtein

Boolean formulae compactly encode huge, constrained search spaces. Thus, variability-intensive systems are often encoded with Boolean formulae. The search space of a variability-intensive system is usually too large to explore without…

Logic in Computer Science · Computer Science 2025-03-19 Olivier Zeyen , Maxime Cordy , Martin Gubri , Gilles Perrouin , Mathieu Acher

Given a multiset $X=\{x_1,..., x_n\}$ of real numbers, the {\it floating-point set summation} problem asks for $S_n=x_1+...+x_n$. Let $E^*_n$ denote the minimum worst-case error over all possible orderings of evaluating $S_n$. We prove that…

Data Structures and Algorithms · Computer Science 2024-09-21 Ming-Yang Kao , Jie Wang

A computer code can simulate a system's propagation of variation from random inputs to output measures of quality. Our aim here is to estimate a critical output tail probability or quantile without a large Monte Carlo experiment. Instead,…

Machine Learning · Statistics 2019-08-16 Hao Chen , William J. Welch

Distribution testing deals with what information can be deduced about an unknown distribution over $\{1,\ldots,n\}$, where the algorithm is only allowed to obtain a relatively small number of independent samples from the distribution. In…

Computational Complexity · Computer Science 2016-09-23 Eldar Fischer , Oded Lachish , Yadu Vasudev

We develop a monitoring procedure to detect changes in a large approximate factor model. Letting $r$ be the number of common factors, we base our statistics on the fact that the $\left( r+1\right) $-th eigenvalue of the sample covariance…

Methodology · Statistics 2022-02-03 Matteo Barigozzi , Lorenzo Trapani

Experimental comparisons of performance represent an important aspect of research on optimization algorithms. In this work we present a methodology for defining the required sample sizes for designing experiments with desired statistical…

Neural and Evolutionary Computing · Computer Science 2018-10-16 Felipe Campelo , Fernanda Takahashi

The purpose of this note is to point out that the theory of expander graphs leads to an interesting test whether $n$ real numbers $x_1, \dots, x_n$ could be $n$ independent samples of a random variable. To any distinct, real numbers $x_1,…

Statistics Theory · Mathematics 2020-08-05 Stefan Steinerberger

Linear models are foundational tools in statistics and ubiquitous across the applied sciences. However, conventional statistical inference -- such as $t$-tests and $F$-tests -- are only valid at fixed sample sizes, making them unsuitable…

Methodology · Statistics 2025-07-08 Michael Lindon , Dae Woong Ham , Martin Tingley , Iavor Bojinov

We present results of an extensive test program of a group of pseudorandom number generators which are commonly used in the applications of physics, in particular in Monte Carlo simulations. The generators include public domain programs,…

High Energy Physics - Lattice · Physics 2009-10-22 I. Vattulainen , K. Kankaala , J. Saarinen , T. Ala-Nissila

A validated simulation model primarily requires performing an appropriate input analysis mainly by determining the behavior of real-world processes using probability distributions. In many practical cases, probability distributions of the…

Applications · Statistics 2014-03-05 Issac Shams , Saeede Ajorlou , Kai Yang

In "Recognizing the Maximum of a Sequence", Gilbert and Mosteller analyze a full information game where n measurements from an uniform distribution are drawn and a player (knowing n) must decide at each draw whether or not to choose that…

Probability · Mathematics 2018-05-30 Marcos Costa Santos Carreira

Many planning and decision activities in logistics and supply chain management are based on forecasts of multiple time dependent factors. Therefore, the quality of planning depends on the quality of the forecasts. We compare various…

Machine Learning · Statistics 2024-06-07 Lena Schmid , Moritz Roidl , Markus Pauly

We consider an online vector balancing game where vectors $v_t$, chosen uniformly at random in $\{-1,+1\}^n$, arrive over time and a sign $x_t \in \{-1,+1\}$ must be picked immediately upon the arrival of $v_t$. The goal is to minimize the…

Data Structures and Algorithms · Computer Science 2020-07-14 Nikhil Bansal , Joel H. Spencer

Large language models increasingly rely on explicit reasoning chains and can produce multiple plausible responses for a given context. We study the candidate sampler that produces the set of plausible responses contrasting the ancestral…

Computation and Language · Computer Science 2025-09-23 Sergey Troshin , Irina Saparina , Antske Fokkens , Vlad Niculae

Constrained-random simulation is the predominant approach used in the industry for functional verification of complex digital designs. The effectiveness of this approach depends on two key factors: the quality of constraints used to…

Logic in Computer Science · Computer Science 2014-03-26 Supratik Chakraborty , Kuldeep S. Meel , Moshe Y. Vardi