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Related papers: A modeler's guide to extreme value software

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Heavy tailed phenomena are naturally analyzed by extreme value statistics. A crucial step in such an analysis is the estimation of the extreme value index, which describes the tail heaviness of the underlying probability distribution. We…

Statistics Theory · Mathematics 2018-07-18 Hanan Ahmed , John H. J. Einmahl

Predictive models are one of the most important techniques that are widely applied in many areas of software engineering. There have been a large number of primary studies that apply predictive models and that present well-preformed studies…

Software Engineering · Computer Science 2020-08-11 Yanming Yang , Xin Xia , David Lo , Tingting Bi , John Grundy , Xiaohu Yang

Data is a cornerstone of empirical software engineering (ESE) research and practice. Data underpin numerous process and project management activities, including the estimation of development effort and the prediction of the likely location…

Software Engineering · Computer Science 2020-12-22 Michael F. Bosu , Stephen G. MacDonell

Extremal dependence between international stock markets is of particular interest in today's global financial landscape. However, previous studies have shown this dependence is not necessarily stationary over time. We concern ourselves with…

Statistical Finance · Quantitative Finance 2017-09-06 Daniela Castro Camilo , Miguel de Carvalho , Jennifer Wadsworth

Software engineering is one of the most recent additions in various disciplines of system engineering. It has emerged as a key obedience of system engineering in a quick succession of time. Various Software Engineering approaches are…

Software Engineering · Computer Science 2010-03-30 Muhammad Javed , Bashir Ahmad , Shahid Hussain , Shakeel Ahmad

Designs conditions for marine structures are typically informed by threshold-based extreme value analyses of oceanographic variables, in which excesses of a high threshold are modelled by a generalized Pareto (GP) distribution. Too low a…

Methodology · Statistics 2016-06-02 Paul Northrop , Nicolas Attalides , Philip Jonathan

This paper deals with the extreme value analysis for the triangular arrays, which appear when some parameters of the mixture model vary as the number of observations grow. When the mixing parameter is small, it is natural to associate one…

Statistics Theory · Mathematics 2021-03-17 Vladimir Panov , Ekaterina Morozova

An intriguing connection between extreme value statistics and traveling fronts has been found recently in a number of diverse problems. In this brief review we outline a few such problems and consider their various applications.

Statistical Mechanics · Physics 2009-11-07 Satya N. Majumdar , P. L. Krapivsky

Numerical simulations of physical systems exhibit discrepancies arising from unmodeled physics and idealizations, as well as numerical approximation errors stemming from discretization and solver tolerances. This article reviews techniques…

Computational Physics · Physics 2026-01-23 Danny Smyl

This article introduces the R package evgam. The package provides functions for fitting extreme value distributions. These include the generalized extreme value and generalized Pareto distributions. The former can also be fitted through a…

Computation · Statistics 2020-11-10 Benjamin D. Youngman

Accurately predicting faulty software units helps practitioners target faulty units and prioritize their efforts to maintain software quality. Prior studies use machine-learning models to detect faulty software code. We revisit past studies…

Software Engineering · Computer Science 2019-01-08 Libo Li , Stefan Lessmann , Bart Baesens

In this paper we are concerned with the analysis of heavy-tailed data when a portion of the extreme values is unavailable. This research was motivated by an analysis of the degree distributions in a large social network. The degree…

Statistics Theory · Mathematics 2018-12-20 Jingjing Zou , Richard A. Davis , Gennady Samorodnitsky

Advances in variational inference enable parameterisation of probabilistic models by deep neural networks. This combines the statistical transparency of the probabilistic modelling framework with the representational power of deep learning.…

Computation and Language · Computer Science 2020-05-05 Tom Pelsmaeker , Wilker Aziz

By the nature of their construction, many statistical models for extremes result in likelihood functions that are computationally prohibitive to evaluate. This is consequently problematic for the purposes of likelihood-based inference. With…

Methodology · Statistics 2014-11-07 Robert Erhardt , Scott A. Sisson

The problem of distinct value estimation has many applications. Being a critical component of query optimizers in databases, it also has high commercial impact. Many distinct value estimators have been proposed, using various statistical…

Databases · Computer Science 2016-12-05 Vinay Deolalikar , Hernan Laffitte

Despite potential benefits in Software Engineering (SE), adoption of software modelling in industry is low. Technical issues such as tool support have gained significant research before, but individual guidance and training have received…

Software Engineering · Computer Science 2022-06-15 Shalini Chakraborty , Grischa Liebel

Scientific results in high-energy physics and in many other fields often rely on complex software stacks. In order to support reproducibility and scrutiny of the results, it is good practice to use open source software and to cite software…

Software Engineering · Computer Science 2014-07-14 Jakob Blomer , Dario Berzano , Predrag Buncic , Ioannis Charalampidis , Gerardo Ganis , George Lestaris , René Meusel

Actually, software products are increasing in a fast way and are used in almost all activities of human life. Consequently measuring and evaluating the quality of a software product has become a critical task for many companies. Several…

Software Engineering · Computer Science 2014-12-10 Jose P. Miguel , David Mauricio , Glen Rodriguez

In this paper we briefly review the main methodological aspects concerned with the application of the Bayesian approach to model choice and model averaging in the context of variable selection in regression models. This includes prior…

Computation · Statistics 2016-12-08 Anabel Forte , Gonzalo Garcia-Donato , Mark Steel

Extreme values of real phenomena are events that occur with low frequency, but can have a large impact on real life. These are, in many practical problems, high-dimensional by nature (e.g. Tawn, 1990; Coles and Tawn, 1991). To study these…

Methodology · Statistics 2015-08-25 Boris Beranger , Simone A. Padoan
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