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We investigate the behavior of the empirical neighbourhood distribution of marked graphs in the framework of local weak convergence. We establish a large deviation principle for such families of empirical measures. The proof builds on…

Probability · Mathematics 2024-01-02 Rangel Baldasso , Alan Pereira , Guilherme Reis

In this paper Raptor code ensembles with linear random precodes in a fixed-rate setting are considered. An expression for the average distance spectrum is derived and this expression is used to obtain the asymptotic exponent of the weight…

Information Theory · Computer Science 2015-04-22 Francisco Lázaro , Enrico Paolini , Gianluigi Liva , Gerhard Bauch

This paper introduces an objective metric for evaluating a parsing scheme. It is based on Shannon's original work with letter sequences, which can be extended to part-of-speech tag sequences. It is shown that this regular language is an…

cmp-lg · Computer Science 2008-02-03 Caroline Lyon , Stephen Brown

Monte Carlo methods, Variational Inference, and their combinations play a pivotal role in sampling from intractable probability distributions. However, current studies lack a unified evaluation framework, relying on disparate performance…

Machine Learning · Computer Science 2024-06-12 Denis Blessing , Xiaogang Jia , Johannes Esslinger , Francisco Vargas , Gerhard Neumann

We consider an extension of the setting of label ranking, in which the learner is allowed to make predictions in the form of partial instead of total orders. Predictions of that kind are interpreted as a partial abstention: If the learner…

Artificial Intelligence · Computer Science 2011-12-05 Weiwei Cheng , Eyke Hüllermeier

Sample measures of top centile contributions to the total (concentration) are downward biased, unstable estimators, extremely sensitive to sample size and concave in accounting for large deviations. It makes them particularly unfit in…

Applications · Statistics 2016-09-05 Nassim N Taleb , Raphael Douady

This paper presents a novel method for finding features in the analysis of variable distributions stemming from time series. We apply the methodology to the case of submitted and accepted papers in peer-reviewed journals. We provide a…

Digital Libraries · Computer Science 2019-10-15 Marcel Ausloos , Olgica Nedic , Aleksandar Dekanski

In this paper, we study some properties and characterization of the general weighted cumulative past extropy (n-WCPJ). Many results including some bounds, inequalities, and effects of linear transformations are obtained. We study the…

Statistics Theory · Mathematics 2023-05-09 Pradeep Kumar Sahu , Nitin Gupta

We submit newly developed citation impact indicators based not on arithmetic averages of citations but on percentile ranks. Citation distributions are-as a rule-highly skewed and should not be arithmetically averaged. With percentile ranks,…

Digital Libraries · Computer Science 2011-06-21 Loet Leydesdorff , Lutz Bornmann , Rüdiger Mutz , Tobias Opthof

In situations where the sampling units in a study can be more easily ranked based on the measurement of an auxiliary variable, ranked set sampling provide unbiased estimators for the mean of a population that they are more efficient than…

Statistics Theory · Mathematics 2014-05-13 Saeid Tahmasebi , Ali Akbar Jafari

A weighted likelihood technique for robust estimation of a multivariate Wrapped Normal distribution for data points scattered on a p-dimensional torus is proposed. The occurrence of outliers in the sample at hand can badly compromise…

Methodology · Statistics 2021-07-01 Giovanni Saraceno , Claudio Agostinelli , Luca Greco

Sparse linear regression is a vast field and there are many different algorithms available to build models. Two new papers published in Statistical Science study the comparative performance of several sparse regression methodologies,…

Machine Learning · Computer Science 2021-02-10 Owais Sarwar , Benjamin Sauk , Nikolaos V. Sahinidis

Social graphs can be easily extracted from Online Social Networks. However these networks are getting larger from day to day. Sampling methods used to evaluate graph information cannot accurately extract graph properties. Furthermore Social…

Social and Information Networks · Computer Science 2013-01-17 Giannis Haralabopoulos , Ioannis Anagnostopoulos

The estimation of a precision matrix is a crucial problem in various research fields, particularly when working with high dimensional data. In such settings, the most common approach is to use the penalized maximum likelihood. The…

Methodology · Statistics 2025-01-10 Vahe Avagyan

Uniform convergence rates are provided for asymptotic representations of sample extremes. These bounds which are universal in the sense that they do not depend on the extreme value index are meant to be extended to arbitrary samples…

We consider a model of random tree growth, where at each time unit a new vertex is added and attached to an already existing vertex chosen at random. The probability with which a vertex with degree $k$ is chosen is proportional to $w(k)$,…

Probability · Mathematics 2007-05-23 Anna Rudas , Balint Toth , Benedek Valko

A uniform recursive tree on $n$ vertices is a random tree where each possible $(n-1)!$ labeled recursive rooted tree is selected with equal probability. In this paper we introduce and study weighted trees, a non-uniform recursive tree model…

Probability · Mathematics 2017-12-12 Ella Hiesmayr , Ümit Işlak

In Basili and Pratelli (2024), a novel and coherent concept of interval probability measures has been introduced, providing a method for representing imprecise probabilities and uncertainty. Within the framework of set algebra, we…

Statistics Theory · Mathematics 2024-04-25 Marcello Basili , Luca Pratelli

This paper investigates the weighted-averaging dynamic for unconstrained and constrained consensus problems. Through the use of a suitably defined adjoint dynamic, quadratic Lyapunov comparison functions are constructed to analyze the…

Optimization and Control · Mathematics 2014-07-30 Angelia Nedich , Ji Liu

A weighted regression procedure is proposed for regression type problems where the innovations are heavy-tailed. This method approximates the least absolute regression method in large samples, and the main advantage will be if the sample is…

Computation · Statistics 2018-11-06 J. Martin van Zyl
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