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Multivariate statistical analysis is concerned with observations on several variables which are thought to possess some degree of inter-dependence. Driven by problems in genetics and the social sciences, it first flowered in the earlier…

Statistics Theory · Mathematics 2007-06-13 Iain M. Johnstone

In recent years, ideas from statistics and scientific computing have begun to interact in increasingly sophisticated and fruitful ways with ideas from computer science and the theory of algorithms to aid in the development of improved…

Data Structures and Algorithms · Computer Science 2010-10-11 Michael W. Mahoney

The K function and its related statistics have been an enduring tool in the analysis of spatial point processes, providing an easy to compute and interpret summary statistic for characterising the interactions between points of one type, or…

Methodology · Statistics 2026-05-20 Jake P. Grainger , Tuomas A. Rajala , David J. Murrell , Sofia C. Olhede

The 175th anniversary of the ASA provides an opportunity to look back into the past and peer into the future. What led our forebears to found the association? What commonalities do we still see? What insights might we glean from their…

Other Statistics · Statistics 2020-07-21 Nicholas Jon Horton

The paper argues that a part of the current statistical discussion is not based on the standard firm foundations of the field. Among the examples we consider are prediction into the future, semi-supervised classification, and causality…

Statistics Theory · Mathematics 2010-03-09 Ya'acov Ritov

Supertagging is an approach originally developed by Bangalore and Joshi (1999) to improve the parsing efficiency. In the beginning, the scholars used small training datasets and somewhat na\"ive smoothing techniques to learn the probability…

Computation and Language · Computer Science 2014-12-22 Taraka Rama K

This comment emphasizes the importance of model checking and model fitting when making inferences about finite population quantities. It also suggests the value of using unit level models when making inferences for small subpopulations,…

Methodology · Statistics 2011-08-22 J. Sedransk

We argue here about the relevance and the ultimate unity of the Bayesian approach in a neutral and agnostic manner. Our main theme is that Bayesian data analysis is an effective tool for handling complex models, as proven by the increasing…

Methodology · Statistics 2010-03-26 Christian P. Robert

This article presents an in-depth educational overview of the latest mathematical developments in coupled cluster (CC) theory, beginning with Schneider's seminal work from 2009 that introduced the first local analysis of CC theory. We offer…

Chemical Physics · Physics 2024-01-17 Fabian M. Faulstich

A new five-parameter continuous distribution which generalizes the Kumaraswamy and the beta distributions as well as some other well-known distributions is proposed and studied. The model has as special cases new four- and three-parameter…

Methodology · Statistics 2010-04-07 Jalmar M. F. Carrasco , Silvia L. P. Ferrari , Gauss M. Cordeiro

This doctoral dissertation presents an in-depth analysis of the first six chapters of Eddington's Fundamental Theory, sometimes referred to as his 'statistical' theory, in the context of discoveries and advancements made since its original…

Quantum Physics · Physics 2007-05-23 I. T. Durham

A brief survey of the author's works on the fundamental conceptual ideas of quantum statistical physics developed by N. N. Bogoliubov and his school was given. The development and applications of the method of quasiaverages to quantum…

History and Philosophy of Physics · Physics 2010-05-07 A. L. Kuzemsky

Instructors of statistics who teach non-statistics majors possess varied academic backgrounds, and hence it is reasonable to expect variability in their content knowledge, and pedagogical approach. The aim of this study was to determine the…

Methodology · Statistics 2010-07-20 Rossi A. Hassad

This is a survey paper on several aspects of differential geometry for the last 30 years, especially in those areas related to non-linear analysis. It grew from a talk I gave on the occasion of seventieth anniversary of Chinese Mathematical…

Differential Geometry · Mathematics 2007-05-23 Shing-Tung Yau

The past decades have seen enormous improvements in computational inference based on statistical models, with continual enhancement in a wide range of computational tools, in competition. In Bayesian inference, first and foremost, MCMC…

Computation · Statistics 2015-05-12 Peter J. Green , Krzysztof Łatuszyński , Marcelo Pereyra , Christian P. Robert

Over the last two decades, significant advances have been made in the design and analysis of fixed-parameter algorithms for a wide variety of graph-theoretic problems. This has resulted in an algorithmic toolbox that is by now…

Data Structures and Algorithms · Computer Science 2021-01-01 Faisal Abu-Khzam , Sebastian Lamm , Matthias Mnich , Alexander Noe , Christian Schulz , Darren Strash

In some estimation problems, especially in applications dealing with information theory, signal processing and biology, theory provides us with additional information allowing us to restrict the parameter space to a finite number of points.…

Methodology · Statistics 2012-07-25 Christine Choirat , Raffaello Seri

Over the last three years, a number of fundamental issues in quantum gravity were addressed in the framework of quantum geometry, discussed extensively by John Baez in this conference. In particular, these include: A statistical mechanical…

Mathematical Physics · Physics 2007-05-23 Abhay Ashtekar

This paper offers a comprehensive introduction to Bayesian inference, combining historical context, theoretical foundations, and core analytical examples. Beginning with Bayes' theorem and the philosophical distinctions between Bayesian and…

Methodology · Statistics 2025-12-08 Juan Sosa , Carlos A. Martínez , Danna Cruz

In this paper, we review some features of quantum annealing and related topics from viewpoints of statistical physics, condensed matter physics, and computational physics. We can obtain a better solution of optimization problems in many…

Disordered Systems and Neural Networks · Physics 2017-08-23 Shu Tanaka , Ryo Tamura