Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
This map shows the geographic impact of Andreas Buja'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 Andreas Buja with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andreas Buja more than expected).
This network shows the impact of papers produced by Andreas Buja. 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 Andreas Buja. The network helps show where Andreas Buja may publish in the future.
Co-authorship network of co-authors of Andreas Buja
This figure shows the co-authorship network connecting the top 25 collaborators of Andreas Buja.
A scholar is included among the top collaborators of Andreas Buja 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 Andreas Buja. Andreas Buja is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
All Works
20 of 20 papers shown
1.
Brown, Lawrence D., et al.. (2021). Semi-Supervised Linear Regression. Journal of the American Statistical Association. 117(540). 2238–2251.19 indexed citations
Buja, Andreas, et al.. (2016). Models as Approximations --- Part II: A General Theory of Model-Robust Regression. arXiv (Cornell University).6 indexed citations
4.
Buja, Andreas, Richard A. Berk, Lawrence D. Brown, et al.. (2015). Models as Approximations - A Conspiracy of Random Regressors and Model Deviations Against Classical Inference in Regression. Statistical Science. 1.4 indexed citations
5.
Buja, Andreas, Richard A. Berk, Lawrence Brown, et al.. (2014). Models as Approximations, Part I: A Conspiracy of Nonlinearity and Random Regressors in Linear Regression. arXiv (Cornell University).8 indexed citations
6.
Buja, Andreas, Richard A. Berk, Lawrence Brown, et al.. (2014). The Conspiracy of Random Predictors and Model Violations against Classical Inference in Regression. arXiv (Cornell University).3 indexed citations
Hosanagar, Kartik, Daniel Fleder, Dokyun Lee, & Andreas Buja. (2013). Will the Global Village Fracture into Tribes? Recommender Systems and their Effects on Consumer Fragmentation. Scholarly Commons (University of Pennsylvania).1 indexed citations
9.
Chen, Lisha & Andreas Buja. (2013). Stress functions for nonlinear dimension reduction, proximity analysis, and graph drawing. Journal of Machine Learning Research. 14(1). 1145–1173.9 indexed citations
Wickham, Hadley, Dianne Cook, Heike Hofmann, & Andreas Buja. (2011). tourr: An R Package for Exploring Multivariate Data with Projections. SHILAP Revista de lepidopterología.9 indexed citations
12.
Swayne, Deborah F., Andreas Buja, Duncan Temple Lang, & Dianne Cook. (2011). GGobi: A data visualization system. ascl.2 indexed citations
Mallows, C. L., David R. Brillinger, Andreas Buja, et al.. (2006). Tukey's Paper After 40 Years, With Discussion. Technometrics. 48.4 indexed citations
15.
Buja, Andreas & Werner Stuetzle. (2006). OBSERVATIONS ON BAGGING. Statistica Sinica. 16(2). 323–351.44 indexed citations
16.
Swayne, Deborah F. & Andreas Buja. (1998). Missing Data in Interactive High-Dimensional Data Visualization. SSRN Electronic Journal.28 indexed citations
17.
Buja, Andreas, Dianne Cook, & Deborah F. Swayne. (1996). Interactive High-Dimensional Data Visualization. Journal of Computational and Graphical Statistics. 5(1). 78–99.210 indexed citations
Buja, Andreas & Daniel Asimov. (1986). Grand tour methods: an outline. 63–67.52 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.