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Markov chain Monte Carlo is an inherently serial algorithm. Although likelihood calculations for individual steps can sometimes be parallelized, the serial evolution of the process is widely viewed as incompatible with parallelization,…

Computation · Statistics 2013-12-31 Douglas N. VanDerwerken , Scott C. Schmidler

Parameter inference is a fundamental problem in data-driven modeling. Given observed data that is believed to be a realization of some parameterized model, the aim is to find parameter values that are able to explain the observed data. In…

Data Structures and Algorithms · Computer Science 2016-04-20 Carlo Albert , Simone Ulzega , Ruedi Stoop

This article presents a new class of generalized transmuted lifetime distributions which includes a large number of lifetime distributions as sub-family. Several important mathematical quantities such as density function, distribution…

Methodology · Statistics 2024-05-21 Alok Kumar Pandey , Alam Ali , Ashok Kumar Pathak

In this paper, we analyze the relative errors that crop up in the various reliability measures due to the tacit assumption that the components are independently working associated with a $n$-component series system or a parallel system…

Statistics Theory · Mathematics 2025-03-28 Subarna Bhattacharjee , Aninda Kumar Nanda , Subhashree Patra

Turing patterns can be observed in reaction-diffusion systems where chemical species have different diffusion constants. In recent years, several studies investigated the effects of noise on Turing patterns and showed that the parameter…

Computational Physics · Physics 2013-10-30 Yang Cao , Radek Erban

A class of random graph models is considered, combining features of exponential-family models and latent structure models, with the goal of retaining the strengths of both of them while reducing the weaknesses of each of them. An open…

Computation · Statistics 2020-07-21 Sergii Babkin , Jonathan Stewart , Xiaochen Long , Michael Schweinberger

Discrete automated processes in industrial and cyber-physical systems often exhibit a repetitive structure in which successive repetitions follow a common trajectory while differing in duration, amplitude, and fine-scale dynamics. Such…

Machine Learning · Statistics 2026-05-14 Elias Reich , Saverio Messineo , Stefan Huber

A defining feature of non-stationary systems is the time dependence of their statistical parameters. Measured time series may exhibit Gaussian statistics on short time horizons, due to the central limit theorem. The sample statistics for…

Data Analysis, Statistics and Probability · Physics 2020-10-08 Rudi Schäfer , Sonja Barkhofen , Thomas Guhr , Hans-Jürgen Stöckmann , Ulrich Kuhl

We investigate stochastic comparisons between exponential family distributions and their mixtures with respect to the usual stochastic order, the hazard rate order, the reversed hazard rate order, and the likelihood ratio order. A general…

Statistics Theory · Mathematics 2009-10-05 Yaming Yu

To describe the nonequilibrium states of a system we introduce a new thermodynamic parameter - the lifetime (the first passage time) of a system. The statistical distributions that can be obtained out of the mesoscopic description…

Chemical Physics · Physics 2007-05-23 V. V. Ryazanov

The work relates to a new way for analysis of one-dimensional stochastic systems, based on consideration of its higher order difference structure. From this point of view, the deterministic and random processes are analyzed. A new numerical…

Chaotic Dynamics · Physics 2016-09-08 A. Yu. Shahverdian , A. V. Apkarian

Stochastic orders are very useful tool to compare the lifetimes of two coherent systems. We show that, under certain conditions, a coherent system of used components performs better (worse) than a used coherent system with respect to…

Applications · Statistics 2016-01-20 Nil Kamal Hazra , Asok K. Nanda

Scale-free networks are abundant in nature and society, describing such diverse systems as the world wide web, the web of human sexual contacts, or the chemical network of a cell. All models used to generate a scale-free topology are…

Statistical Mechanics · Physics 2009-11-07 Albert-Laszlo Barabasi , Erzsebet Ravasz , Tamas Vicsek

Stochastic blockmodels provide a convenient representation of relations between communities of nodes in a network. However, they imply a notion of stochastic equivalence that is often unrealistic for real networks, and they comprise large…

Methodology · Statistics 2017-10-17 Mirko Signorelli

The Gompertz-Makeham distribution, which is used commonly to represent lifetimes based on laws of mortality, is one of the most popular choices for mortality modelling in the field of actuarial science. This paper investigates ordering…

Applications · Statistics 2019-12-10 Amarjit Kundu , Shovan Chowdhury , Narayanaswamy Balakrishnan

With the advent of structured data in the form of social networks, genetic circuits and protein interaction networks, statistical analysis of networks has gained popularity over recent years. Stochastic block model constitutes a classical…

Statistics Theory · Mathematics 2015-05-27 Debdeep Pati , Anirban Bhattacharya

Many problems in the geophysical sciences demand the ability to calibrate the parameters and predict the time evolution of complex dynamical models using sequentially-collected data. Here we introduce a general methodology for the joint…

Computation · Statistics 2018-12-12 Sara Pérez-Vieites , Inés P. Mariño , Joaquín Míguez

We introduce some new generalized stochastic orderings (in the spirit of relative ageing) which compare probability distributions with the exponential distribution. These orderings are useful to understand the phenomenon of positive ageing…

Applications · Statistics 2014-10-21 Nil Kamal Hazra , Asok K. Nanda

This paper proposes a method for generating typical scenarios based on system-level macroscopic characteristics of power system and considering its stability properties. First, considering uncertainties such as renewable energy generation…

Systems and Control · Electrical Eng. & Systems 2026-04-02 Tao Li , Chen Shen

We study the relationship between topological scales and dynamic time scales in complex networks. The analysis is based on the full dynamics towards synchronization of a system of coupled oscillators. In the synchronization process, modular…

Disordered Systems and Neural Networks · Physics 2009-11-11 Alex Arenas , Albert Diaz-Guilera , Conrad J. Perez-Vicente