|
Simplicial Depth
In robust statistics and computational geometry, simplicial depth is a measure of central tendency determined by the simplices that contain a given point. For the Euclidean plane, it counts the number of triangles of sample points that contain a given point. Definition The simplicial depth of a point p in d-dimensional Euclidean space, with respect to a set of sample points in that space, is the number of d-dimensional simplices (the convex hulls of sets of d+1 sample points) that contain p. The same notion can be generalized to any probability distribution on points of the plane, not just the empirical distribution given by a set of sample points, by defining the depth to be the probability that a randomly chosen (d+1)-tuple of points has a convex hull that This probability can be calculated, from the number of simplices that by dividing by \tbinom where n is the number of sample points. Under the standard definition of simplicial depth, the simplices that have p on their bou ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Approximation Algorithm
In computer science and operations research, approximation algorithms are efficient algorithms that find approximate solutions to optimization problems (in particular NP-hard problems) with provable guarantees on the distance of the returned solution to the optimal one. Approximation algorithms naturally arise in the field of theoretical computer science as a consequence of the widely believed P ≠NP conjecture. Under this conjecture, a wide class of optimization problems cannot be solved exactly in polynomial time. The field of approximation algorithms, therefore, tries to understand how closely it is possible to approximate optimal solutions to such problems in polynomial time. In an overwhelming majority of the cases, the guarantee of such algorithms is a multiplicative one expressed as an approximation ratio or approximation factor i.e., the optimal solution is always guaranteed to be within a (predetermined) multiplicative factor of the returned solution. However, there are ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Annals Of Statistics
The ''Annals of Statistics'' is a peer-reviewed statistics journal published by the Institute of Mathematical Statistics. It was started in 1973 as a continuation in part of the '' Annals of Mathematical Statistics (1930)'', which was split into the ''Annals of Statistics'' and the '' Annals of Probability''. The journal CiteScore is 5.8, and its SCImago Journal Rank is 5.877, both from 2020. Articles older than 3 years are available on JSTOR, and all articles since 2004 are freely available on the arXiv. Editorial board The following persons have been editors of the journal: * Ingram Olkin (1972–1973) * I. Richard Savage (1974–1976) * Rupert Miller (1977–1979) * David V. Hinkley (1980–1982) * Michael D. Perlman (1983–1985) * Willem van Zwet (1986–1988) * Arthur Cohen (1988–1991) * Michael Woodroofe (1992–1994) * Larry Brown and John Rice (1995–1997) * Hans-Rudolf Künsch and James O. Berger (1998–2000) * John Marden and Jon A. Wellner (2001–2003 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Proceedings Of The National Academy Of Sciences Of The United States Of America
''Proceedings of the National Academy of Sciences of the United States of America'' (often abbreviated ''PNAS'' or ''PNAS USA'') is a peer-reviewed multidisciplinary scientific journal. It is the official journal of the National Academy of Sciences, published since 1915, and publishes original research, scientific reviews, commentaries, and letters. According to '' Journal Citation Reports'', the journal has a 2021 impact factor of 12.779. ''PNAS'' is the second most cited scientific journal, with more than 1.9 million cumulative citations from 2008 to 2018. In the mass media, ''PNAS'' has been described variously as "prestigious", "sedate", "renowned" and "high impact". ''PNAS'' is a delayed open access journal, with an embargo period of six months that can be bypassed for an author fee ( hybrid open access). Since September 2017, open access articles are published under a Creative Commons license. Since January 2019, ''PNAS'' has been online-only, although print issues a ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Information Processing Letters
''Information Processing Letters'' is a peer reviewed scientific journal in the field of computer science, published by Elsevier. The aim of the journal is to enable fast dissemination of results in the field of information processing Information processing is the change (processing) of information in any manner detectable by an observer. As such, it is a process that ''describes'' everything that happens (changes) in the universe, from the falling of a rock (a change in posi ... in the form of short papers. Submissions are limited to nine double-spaced pages. Both theoretical and experimental research is covered. External links * Computer science journals Publications established in 1971 Semi-monthly journals Elsevier academic journals {{compu-journal-stub ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Discrete Mathematics (journal)
''Discrete Mathematics'' is a biweekly peer-reviewed scientific journal in the broad area of discrete mathematics, combinatorics, graph theory, and their applications. It was established in 1971 and is published by North-Holland Publishing Company. It publishes both short notes, full length contributions, as well as survey articles. In addition, the journal publishes a number of special issues each year dedicated to a particular topic. Although originally it published articles in French and German, it now allows only English language articles. The editor-in-chief is Douglas West ( University of Illinois, Urbana). History The journal was established in 1971. The very first article it published was written by Paul Erdős, who went on to publish a total of 84 papers in the journal. Abstracting and indexing The journal is abstracted and indexed in: According to the ''Journal Citation Reports'', the journal has a 2020 impact factor of 0.87. Notable publications * The 1972 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ACM Transactions On Algorithms
''ACM Transactions on Algorithms'' (''TALG'') is a quarterly peer-reviewed scientific journal covering the field of algorithms. It was established in 2005 and is published by the Association for Computing Machinery. The editor-in-chief is Edith Cohen. The journal was created when the editorial board of the ''Journal of Algorithms'' resigned out of protest to the pricing policies of the publisher, Elsevier. Apart from regular submissions, the journal also invites selected papers from the ''ACM-SIAM Symposium on Discrete Algorithms (SODA)''. Abstracting and indexing The journal is abstracted and indexed in the Science Citation Index Expanded, Current Contents/Engineering, Computing & Technology, and Scopus. According to the ''Journal Citation Reports'', the journal has a 2020 impact factor of 1.104. Past editors The following persons have been editors-in-chief of the journal: * Harold N. Gabow (2005-2008) * Susanne Albers (2008-2014) * Aravind Srinivasan (2014-2021) See also ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Computational Statistics & Data Analysis
''Computational Statistics & Data Analysis'' is a monthly peer-reviewed scientific journal covering research on and applications of computational statistics Computational statistics, or statistical computing, is the bond between statistics and computer science. It means statistical methods that are enabled by using computational methods. It is the area of computational science (or scientific comput ... and data analysis. The journal was established in 1983 and is the official journal of the International Association for Statistical Computing, a section of the International Statistical Institute. See also * List of statistics journals References External links * {{DEFAULTSORT:Computational Statistics And Data Analysis International Statistical Institute Statistics journals Publications established in 1983 Monthly journals English-language journals Elsevier academic journals * ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Ball (mathematics)
In mathematics, a ball is the solid figure bounded by a ''sphere''; it is also called a solid sphere. It may be a closed ball (including the boundary points that constitute the sphere) or an open ball (excluding them). These concepts are defined not only in three-dimensional Euclidean space but also for lower and higher dimensions, and for metric spaces in general. A ''ball'' in dimensions is called a hyperball or -ball and is bounded by a ''hypersphere'' or ()-sphere. Thus, for example, a ball in the Euclidean plane is the same thing as a disk, the area bounded by a circle. In Euclidean 3-space, a ball is taken to be the volume bounded by a 2-dimensional sphere. In a one-dimensional space, a ball is a line segment. In other contexts, such as in Euclidean geometry and informal use, ''sphere'' is sometimes used to mean ''ball''. In the field of topology the closed n-dimensional ball is often denoted as B^n or D^n while the open n-dimensional ball is \operatorname B^n o ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Spherical Depth
A sphere () is a geometrical object that is a three-dimensional analogue to a two-dimensional circle. A sphere is the set of points that are all at the same distance from a given point in three-dimensional space.. That given point is the centre of the sphere, and is the sphere's radius. The earliest known mentions of spheres appear in the work of the ancient Greek mathematicians. The sphere is a fundamental object in many fields of mathematics. Spheres and nearly-spherical shapes also appear in nature and industry. Bubbles such as soap bubbles take a spherical shape in equilibrium. The Earth is often approximated as a sphere in geography, and the celestial sphere is an important concept in astronomy. Manufactured items including pressure vessels and most curved mirrors and lenses are based on spheres. Spheres roll smoothly in any direction, so most balls used in sports and toys are spherical, as are ball bearings. Basic terminology As mentioned earlier is the spher ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
ε-net (computational Geometry)
An ''ε''-net (pronounced epsilon-net) in computational geometry is the approximation of a general set by a collection of simpler subsets. In probability theory it is the approximation of one probability distribution by another. Background Let ''X'' be a set and R be a set of subsets of ''X''; such a pair is called a ''range space'' or hypergraph, and the elements of ''R'' are called ''ranges'' or ''hyperedges''. An ε-net of a subset ''P'' of ''X'' is a subset ''N'' of ''P'' such that any range ''r'' ∈ R with , ''r'' ∩ ''P'', ≥ ''ε'', ''P'', intersects ''N''. In other words, any range that intersects at least a proportion ε of the elements of ''P'' must also intersect the ''ε''-net ''N''. For example, suppose ''X'' is the set of points in the two-dimensional plane, ''R'' is the set of closed filled rectangles (products of closed intervals), and ''P'' is the unit square , 1nbsp;× , 1 Then the set N consis ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Robust Statistics
Robust statistics are statistics with good performance for data drawn from a wide range of probability distributions, especially for distributions that are not normal. Robust statistical methods have been developed for many common problems, such as estimating location, scale, and regression parameters. One motivation is to produce statistical methods that are not unduly affected by outliers. Another motivation is to provide methods with good performance when there are small departures from a parametric distribution. For example, robust methods work well for mixtures of two normal distributions with different standard deviations; under this model, non-robust methods like a t-test work poorly. Introduction Robust statistics seek to provide methods that emulate popular statistical methods, but which are not unduly affected by outliers or other small departures from model assumptions. In statistics, classical estimation methods rely heavily on assumptions which are often not ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
