Journal of Computational and Graphical Statistics

The Journal of Computational and Graphical Statistics is a quarterly peer-reviewed scientific journal published by Taylor & Francis on behalf of the American Statistical Association. Established in 1992, the journal covers the use of computational and graphical methods in statistics and data analysis, including numerical methods, graphical displays and methods, and perception. It is published jointly with the Institute of Mathematical Statistics and the Interface Foundation of North America. According to the Journal Citation Reports, the journal has a 2017 impact factor of 1.790.

Journal of Computational and Graphical Statistics
DisciplineStatistics
LanguageEnglish
Edited byDianne Cook
Publication details
Publication history
1992-present
Publisher
FrequencyQuarterly
1.790
Standard abbreviations
J. Comput. Graph. Stat.
J. Comput. Graph. Statist.
Indexing
ISSN1061-8600 (print)
1537-2715 (web)
LCCN92642563
OCLC no.901043326
Links

See also

External links

American Statistical Association

The American Statistical Association (ASA) is the main professional organization for statisticians and related professionals in the United States. It was founded in Boston, Massachusetts on November 27, 1839, and is the second oldest continuously operating professional society in the US (only the Massachusetts Medical Society, founded in 1781, is older). The ASA services statisticians, quantitative scientists, and users of statistics across many academic areas and applications.

Brownian surface

A Brownian surface is a fractal surface generated via a fractal elevation function.As with Brownian motion, Brownian surfaces are named after 19th-century biologist Robert Brown.

Computational statistics

Computational statistics, or statistical computing, is the interface between statistics and computer science. It is the area of computational science (or scientific computing) specific to the mathematical science of statistics. This area is also developing rapidly, leading to calls that a broader concept of computing should be taught as part of general statistical education.As in traditional statistics the goal is to transform raw data into knowledge, but the focus lies on computer intensive statistical methods, such as cases with very large sample size and non-homogeneous data sets.The terms 'computational statistics' and 'statistical computing' are often used interchangeably, although Carlo Lauro (a former president of the International Association for Statistical Computing) proposed making a distinction, defining 'statistical computing' as "the application of computer science to statistics",

and 'computational statistics' as "aiming at the design of algorithm for implementing

statistical methods on computers, including the ones unthinkable before the computer

age (e.g. bootstrap, simulation), as well as to cope with analytically intractable problems" [sic].The term 'Computational statistics' may also be used to refer to computationally intensive statistical methods including resampling methods, Markov chain Monte Carlo methods, local regression, kernel density estimation, artificial neural networks and generalized additive models.

Contour boxplot

In statistical graphics and scientific visualization, the contour boxplot is an exploratory tool that has been proposed for visualizing ensembles of feature-sets determined by a threshold on some scalar function (e.g. level-sets, isocontours). Analogous to the classical boxplot and considered an expansion of the concepts defining functional boxplot, the descriptive statistics of a contour boxplot are: the envelope of the 50% central region, the median curve and the maximum non-outlying envelope.

To construct a contour boxplot, data ordering is the first step. In functional data analysis, each observation is a real function, therefore data ordering is different from the classical boxplot where scalar data are simply ordered from the smallest sample value to the largest. More generally, data depth, gives a center-outward ordering of data points, and thereby provides a mechanism for constructing rank statistics of various kinds of multidimensional data. For instance, functional data examples can be ordered using the method of band depth or a modified band depth. In contour data analysis, each observation is a feature-set (a subset of the domain), and therefore not a function. Thus, the notion of band depth and modified band depth is further extended to accommodate features that can be expressed as sets but not necessarily as functions. Contour band depth allows for ordering feature-set data from the center outwards and, thus, introduces a measure to define functional quantiles and the centrality or outlyingness of an observation. Having the ranks of feature-set data, the contour boxplot is a natural extension of the classical boxplot which in special cases reduces back to the traditional functional boxplot.

David Ríos Insua

David Ríos Insua (born June 21, 1964 in Madrid) is a Spanish mathematician, and son and disciple of Sixto Ríos, the "father of Spanish statistics." He is currently also the youngest Fellow of the Spanish Royal Academy of Sciences (de la Real Academia de Ciencias Exactas, Físicas y Naturales, RAC), which he joined in 2008. He received a PhD in Computational Sciences at the University of Leeds. He is Full Professor of the Statistics and Operations Research Department at Rey Juan Carlos University (URJC), and he has been Vice-dean of New Technologies and International Relationships at URJC (2002–2009). He has worked in fields such as Bayesian inference in neuronal networks, MCMC methods in decision analysis, Bayesian robustness or adversarial risk analysis. He has also worked in applied areas such as Electronic Democracy, reservoirs management, counterterrorism model and many others. He is married and has two daughters.

Dianne Cook (statistician)

Dianne Helen Cook is an Australian statistician, the editor of the Journal of Computational and Graphical Statistics, and an expert on the visualization of high-dimensional data. She is professor emeritus of statistics at Iowa State University, and Professor of Business Analytics in the Department of Econometrics and Business Statistics at Monash University.Cook grew up in Wauchope, New South Wales as an athletic farm girl, the first woman to play on her local (men's) cricket team. She was accepted to Sydney University, but instead studied statistics at the closer University of New England (Australia), where she earned a BSc and Dip.Ed. in 1982.

She completed her PhD in 1993 at Rutgers University; her dissertation, supervised jointly by Andreas Buja and Javier Cabrera, was Grand Tour and Projection Pursuit.

She joined the Iowa State faculty in 1993, and remained there until her move to Monash in 2015.

At Iowa State, her students have included Hadley Wickham and Yihui Xie.She is one of the developers of GGobi, and with Deborah F. Swayne, she is the author of Interactive and Dynamic Graphics for Data Analysis: With R and GGobi (Springer, 2007).She is a Fellow of the American Statistical Association.

Exponential random graph models

Exponential random graph models (ERGMs) are a family of statistical models for analyzing data about social and other networks.

Functional boxplot

In statistical graphics, the functional boxplot is an informative exploratory tool that has been proposed for visualizing functional data. Analogous to the classical boxplot, the descriptive statistics of a functional boxplot are: the envelope of the 50% central region, the median curve and the maximum non-outlying envelope.

To construct a functional boxplot, data ordering is the first step. In functional data analysis, each observation is a real function, therefore, different from the classical boxplot where data are simply ordered from the smallest sample value to the largest, in a functional boxplot, functional data, e.g. curves or images, are ordered by a notion of band depth or a modified band depth. It allows for ordering functional data from the center outwards and, thus, introduces a measure to define functional quantiles and the centrality or outlyingness of an observation. Having the ranks of functional data, the functional boxplot is a natural extension of the classical boxplot.

GGobi

GGobi is a free statistical software tool for interactive data visualization. GGobi allows extensive exploration of the data with Interactive dynamic graphics. It is also a tool for looking at multivariate data. R can be used in sync with GGobi (through rggobi). GGobi prides itself on its ability to link multiple graphs together.

Hadley Wickham

Hadley Wickham is a statistician from New Zealand who is currently Chief Scientist at RStudio and an adjunct Professor of statistics at the University of Auckland, Stanford University, and Rice University. He is best known for his development of open-source statistical analysis software packages for R (programming language) that implement logics of data visualisation and data transformation. Wickham's packages and writing are known for advocating a tidy data approach to data import, analysis and modelling methods.

Heat map

A heat map (or heatmap) is a graphical representation of data where the individual values contained in a matrix are represented as colors. "Heat map" is a newer term but shading matrices have existed for over a century.

Hui Zou

Hui Zou is currently a Professor of Statistics at the University of Minnesota.

Institute of Mathematical Statistics

The Institute of Mathematical Statistics is an international professional and scholarly society devoted to the development, dissemination, and application of statistics and probability. The Institute currently has about 4,000 members in all parts of the world. Beginning in 2005, the institute started offering joint membership with the Bernoulli Society for Mathematical Statistics and Probability as well as with the International Statistical Institute. The Institute was founded in 1935 with Harry C. Carver and Henry L. Rietz as its two most important supporters.

Jenny Bryan

Jennifer (Jenny) Bryan is a data scientist and an associate professor of statistics at the University of British Columbia where she developed the Master of Data Science Program. She is a statistician and software engineer at RStudio from Vancouver, Canada and is known for creating open source tools which connect R to Google Sheets and Google Drive.

List of statistics journals

This is a list of scientific journals published in the field of statistics.

MM algorithm

The MM algorithm is an iterative optimization method which exploits the convexity of a function in order to find their maxima or minima. The MM stands for “Majorize-Minimization” or “Minorize-Maximization”, depending on whether the desired optimization is a maximization or a minimization. MM itself is not an algorithm, but a description of how to construct an optimization algorithm.

The expectation–maximization algorithm can be treated as a special case of the MM algorithm.

However, in the EM algorithm conditional expectations are usually involved, while in the MM algorithm convexity and inequalities are the main focus, and it is easier to understand and apply in most cases.

Michael Friendly

Michael Louis Friendly (born 1945) is an American psychologist, Professor of Psychology at York University in Ontario, Canada, and director of its Statistical Consulting Service, especially known for his contributions to graphical methods for categorical and multivariate data, and on the history of data and information visualisation.

Robert Gentleman (statistician)

Robert Clifford Gentleman (born 1959) is a Canadian statistician and bioinformatician currently vice president of computational biology at 23andMe. He is recognized, along with Ross Ihaka, as one of the originators of the R programming language and the Bioconductor project.

Scatter plot

A scatter plot (also called a scatterplot, scatter graph, scatter chart, scattergram, or scatter diagram) is a type of plot or mathematical diagram using Cartesian coordinates to display values for typically two variables for a set of data. If the points are color-coded, one additional variable can be displayed.

The data are displayed as a collection of points, each having the value of one variable determining the position on the horizontal axis and the value of the other variable determining the position on the vertical axis.

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