James R. Schott

2.6k total citations · 1 hit paper
46 papers, 1.6k citations indexed

About

James R. Schott is a scholar working on Statistics and Probability, Management Science and Operations Research and Analytical Chemistry. According to data from OpenAlex, James R. Schott has authored 46 papers receiving a total of 1.6k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistics and Probability, 10 papers in Management Science and Operations Research and 8 papers in Analytical Chemistry. Recurrent topics in James R. Schott's work include Advanced Statistical Methods and Models (25 papers), Optimal Experimental Design Methods (9 papers) and Statistical Methods and Inference (8 papers). James R. Schott is often cited by papers focused on Advanced Statistical Methods and Models (25 papers), Optimal Experimental Design Methods (9 papers) and Statistical Methods and Inference (8 papers). James R. Schott collaborates with scholars based in United States. James R. Schott's co-authors include Karen Kafadar, G. W. Stewart, Mohamed Abdel‐Aty, David A. Harville, John G. Saw, Anthony Vodacek, Robert L. Kremens, Don J. Latham and Mortaza Jamshidian and has published in prestigious journals such as Journal of the American Statistical Association, Biometrika and International Journal of Remote Sensing.

In The Last Decade

James R. Schott

44 papers receiving 1.6k citations

Hit Papers

Matrix Analysis for Statistics. 1997 2026 2006 2016 1997 100 200 300 400 500
What are hit papers?

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.

  1. Matrix Analysis for Statistics.
    1997 561 citations James R. Schott et al. Journal of the American Statistical Association profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
James R. Schott United States 19 745 346 142 133 130 46 1.6k
Leandro Pardo Spain 20 1.3k 1.8× 486 1.4× 62 0.4× 80 0.6× 56 0.4× 202 2.2k
Ronald W. Butler United States 19 792 1.1× 356 1.0× 33 0.2× 36 0.3× 99 0.8× 83 1.6k
Morris L. Eaton United States 22 1.2k 1.6× 536 1.5× 33 0.2× 170 1.3× 94 0.7× 71 2.3k
Sadanori Konishi Japan 20 898 1.2× 469 1.4× 27 0.2× 57 0.4× 63 0.5× 88 1.9k
Arjun K. Gupta United States 16 1.0k 1.3× 442 1.3× 46 0.3× 55 0.4× 80 0.6× 97 1.9k
George R. Terrell United States 13 631 0.8× 503 1.5× 19 0.1× 50 0.4× 87 0.7× 26 1.5k
Edward J. Dudewicz United States 23 1.2k 1.7× 407 1.2× 42 0.3× 106 0.8× 54 0.4× 112 2.3k
Y. L. Tong United States 16 678 0.9× 248 0.7× 201 1.4× 85 0.6× 27 0.2× 56 1.8k
H. D. Brunk United States 19 1.1k 1.5× 557 1.6× 37 0.3× 171 1.3× 82 0.6× 50 2.3k
Brett Presnell United States 13 705 0.9× 361 1.0× 36 0.3× 37 0.3× 50 0.4× 37 1.3k

Countries citing papers authored by James R. Schott

Since Specialization
Citations

This map shows the geographic impact of James R. Schott'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 James R. Schott with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites James R. Schott more than expected).

Fields of papers citing papers by James R. Schott

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by James R. Schott. 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 James R. Schott. The network helps show where James R. Schott may publish in the future.

Co-authorship network of co-authors of James R. Schott

This figure shows the co-authorship network connecting the top 25 collaborators of James R. Schott. A scholar is included among the top collaborators of James R. Schott 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 James R. Schott. James R. Schott 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.
Schott, James R.. (2016). Some tests for the allometric extension model in regression. Communication in Statistics- Theory and Methods. 46(12). 6112–6118. 1 indexed citations
2.
Schott, James R.. (2007). Some high-dimensional tests for a one-way MANOVA. Journal of Multivariate Analysis. 98(9). 1825–1839. 55 indexed citations
3.
Schott, James R.. (2007). A test for the equality of covariance matrices when the dimension is large relative to the sample sizes. Computational Statistics & Data Analysis. 51(12). 6535–6542. 97 indexed citations
4.
Schott, James R.. (2006). Testing the equality of correlation matrices when sample correlation matrices are dependent. Journal of Statistical Planning and Inference. 137(6). 1992–1997. 5 indexed citations
5.
Schott, James R.. (2005). A high-dimensional test for the equality of the smallest eigenvalues of a covariance matrix. Journal of Multivariate Analysis. 97(4). 827–843. 43 indexed citations
6.
Schott, James R.. (2003). Kronecker product permutation matrices and their application to moment matrices of the normal distribution. Journal of Multivariate Analysis. 87(1). 177–190. 18 indexed citations
7.
Schott, James R.. (2003). Weighted chi-squared tests for partial common principal component subspaces. Biometrika. 90(2). 411–421. 4 indexed citations
8.
9.
Schott, James R.. (2002). Principles of Multivariate Analysis: A User's Perspective. Journal of the American Statistical Association. 97(458). 657–658. 49 indexed citations
10.
Schott, James R.. (2002). Testing for elliptical symmetry in covariance-matrix-based analyses. Statistics & Probability Letters. 60(4). 395–404. 27 indexed citations
11.
Schott, James R.. (1999). A test for proportional covariance matrices. Computational Statistics & Data Analysis. 32(2). 135–146. 10 indexed citations
12.
Schott, James R. & G. W. Stewart. (1999). Matrix Algorithms, Volume 1: Basic Decompositions. Journal of the American Statistical Association. 94(448). 1388–1388. 110 indexed citations
13.
Schott, James R.. (1994). Determining the Dimensionality in Sliced Inverse Regression. Journal of the American Statistical Association. 89(425). 141–141. 31 indexed citations
14.
Schott, James R.. (1994). Determining the Dimensionality in Sliced Inverse Regression. Journal of the American Statistical Association. 89(425). 141–148. 90 indexed citations
15.
Schott, James R.. (1991). Testing for the redundancy of variables in principal components analysis. Statistics & Probability Letters. 11(6). 495–501. 4 indexed citations
16.
Schott, James R.. (1990). Canonical mean projections and confidence regions in canonical variate analysis. Biometrika. 77(3). 587–596. 6 indexed citations
17.
Schott, James R.. (1988). Testing the equality of the smallest latent roots of a correlation matrix. Biometrika. 75(4). 794–796. 5 indexed citations
18.
Schott, James R.. (1986). A note on the critical values used in stepwise tests for multiplicative components of interaction. Communication in Statistics- Theory and Methods. 15(5). 1561–1570. 21 indexed citations
19.
Schott, James R. & John G. Saw. (1984). A multivariate one-way classification model with random effects. Journal of Multivariate Analysis. 15(1). 1–12. 19 indexed citations
20.
Schott, James R.. (1984). Optimal bounds for the distributions of some test criteria for tests of dimensionality. Biometrika. 71(3). 561–567. 20 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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