Karen Vines

3.9k total citations · 1 hit paper
14 papers, 2.6k citations indexed

About

Karen Vines is a scholar working on Statistics and Probability, Computer Vision and Pattern Recognition and Obstetrics and Gynecology. According to data from OpenAlex, Karen Vines has authored 14 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Statistics and Probability, 2 papers in Computer Vision and Pattern Recognition and 2 papers in Obstetrics and Gynecology. Recurrent topics in Karen Vines's work include Pregnancy and preeclampsia studies (2 papers), Sensory Analysis and Statistical Methods (2 papers) and Statistics Education and Methodologies (2 papers). Karen Vines is often cited by papers focused on Pregnancy and preeclampsia studies (2 papers), Sensory Analysis and Statistical Methods (2 papers) and Statistics Education and Methodologies (2 papers). Karen Vines collaborates with scholars based in United Kingdom, Netherlands and United States. Karen Vines's co-authors include Martyn Plummer, Nicky Best, Deepayan Sarkar, Árni Magnússon, Douglas M. Bates, Russell G. Almond, Bradley E. Sturgeon, Steven J. Peters, Cheryl D. Stevenson and Michel van de Velden and has published in prestigious journals such as The Journal of Physical Chemistry, Food Quality and Preference and Ultrasound in Obstetrics and Gynecology.

In The Last Decade

Karen Vines

13 papers receiving 2.5k citations

Hit Papers

CODA: convergence diagnosis and output analysis for MCMC 2006 2026 2012 2019 2006 500 1000 1.5k 2.0k

Peers

Karen Vines
Katalin Csilléry Switzerland
Uwe Ligges Germany
Robert V. Foutz United States
Lynn Kuo United States
Wenyang Zhang United States
David Welch New Zealand
Thomas W. Yee New Zealand
M.W. Feldman United States
Kevin McConway United Kingdom
Katalin Csilléry Switzerland
Karen Vines
Citations per year, relative to Karen Vines Karen Vines (= 1×) peers Katalin Csilléry

Countries citing papers authored by Karen Vines

Since Specialization
Citations

This map shows the geographic impact of Karen Vines's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Karen Vines with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Karen Vines more than expected).

Fields of papers citing papers by Karen Vines

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Karen Vines. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Karen Vines. The network helps show where Karen Vines may publish in the future.

Co-authorship network of co-authors of Karen Vines

This figure shows the co-authorship network connecting the top 25 collaborators of Karen Vines. A scholar is included among the top collaborators of Karen Vines based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Karen Vines. Karen Vines is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

14 of 14 papers shown
2.
Hilliam, Rachel & Karen Vines. (2021). When one size does fit all: Simultaneous delivery of statistics teaching to multiple audiences. Journal of University Teaching and Learning Practice. 18(2). 1 indexed citations
3.
Hilliam, Rachel & Karen Vines. (2021). When one size does fit all: Simultaneous delivery of statistics teaching to multiple audiences. Research Online (University of Wollongong). 18(2). 4. 1 indexed citations
4.
Plummer, Martyn, Nicky Best, Karen Vines, et al.. (2020). Output Analysis and Diagnostics for MCMC [R package coda version 0.19-4]. 7 indexed citations
5.
Vines, Karen, et al.. (2019). Sonification of numerical data for education. Open Learning The Journal of Open Distance and e-Learning. 34(1). 19–39. 14 indexed citations
6.
Plummer, Martyn, Nicky Best, Karen Vines, et al.. (2015). Output Analysis and Diagnostics for MCMC. 41 indexed citations
7.
Gower, J. C., Patrick J. F. Groenen, Michel van de Velden, & Karen Vines. (2014). Better perceptual maps: Introducing explanatory icons to facilitate interpretation. Food Quality and Preference. 36. 61–69. 5 indexed citations
8.
Gower, J. C., Patrick J. F. Groenen, Michel van de Velden, & Karen Vines. (2010). Perceptual maps: the good, the bad and the ugly. RePub (Erasmus University Rotterdam). 3 indexed citations
9.
Trendafilov, Nickolay T. & Karen Vines. (2008). Simple and interpretable discrimination. Computational Statistics & Data Analysis. 53(4). 979–989. 1 indexed citations
10.
Plummer, Martyn, et al.. (2006). CODA: convergence diagnosis and output analysis for MCMC. Open Research Online (The Open University). 2488 indexed citations breakdown →
11.
Vines, Karen, et al.. (2004). Time domain measurement of blood flow in the human fetal aorta during normal pregnancy. Ultrasound in Obstetrics and Gynecology. 23(3). 257–261. 4 indexed citations
13.
Vines, Karen, Ronald F. Evilia, & Scott L. Whittenburg. (1992). Improved resolution of spectral splittings via bayesian spectral analysis. Journal of Magnetic Resonance (1969). 100(1). 195–201. 2 indexed citations
14.
Stevenson, Cheryl D., Bradley E. Sturgeon, Karen Vines, & Steven J. Peters. (1988). Separation of benzene and deuterium-substituted benzene via potassium reduction. The Journal of Physical Chemistry. 92(23). 6850–6852. 16 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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