John Gurland

2.7k total citations
89 papers, 1.7k citations indexed

About

John Gurland is a scholar working on Statistics and Probability, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, John Gurland has authored 89 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 47 papers in Statistics and Probability, 15 papers in Artificial Intelligence and 13 papers in Management Science and Operations Research. Recurrent topics in John Gurland's work include Statistical Distribution Estimation and Applications (35 papers), Advanced Statistical Methods and Models (26 papers) and Bayesian Methods and Mixture Models (14 papers). John Gurland is often cited by papers focused on Statistical Distribution Estimation and Applications (35 papers), Advanced Statistical Methods and Models (26 papers) and Bayesian Methods and Mixture Models (14 papers). John Gurland collaborates with scholars based in United States, Nigeria and India. John Gurland's co-authors include Ram C. Tripathi, Ram C. Dahiya, J. S. Mehta, Austin F. S. Lee, S. K. Katti, P. Armitage, Jayaram Sethuraman, Malcolm E. Turner, Paul A. Dahm and Paul N. Hinz and has published in prestigious journals such as JAMA, Journal of the American Statistical Association and Econometrica.

In The Last Decade

John Gurland

87 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John Gurland United States 25 885 376 268 186 145 89 1.7k
H. D. Brunk United States 19 1.1k 1.3× 557 1.5× 353 1.3× 219 1.2× 171 1.2× 50 2.3k
Gerald S. Rogers United States 13 837 0.9× 455 1.2× 391 1.5× 336 1.8× 79 0.5× 30 1.9k
P. C. Consul Canada 19 1.0k 1.1× 556 1.5× 196 0.7× 193 1.0× 81 0.6× 61 1.7k
L. R. Shenton United States 18 710 0.8× 273 0.7× 171 0.6× 190 1.0× 99 0.7× 104 1.5k
C. D. Kemp United Kingdom 18 593 0.7× 349 0.9× 190 0.7× 132 0.7× 56 0.4× 55 1.6k
H. E. Daniels United Kingdom 20 902 1.0× 408 1.1× 214 0.8× 362 1.9× 119 0.8× 54 2.0k
Morris L. Eaton United States 22 1.2k 1.3× 536 1.4× 446 1.7× 270 1.5× 279 1.9× 71 2.3k
F. T. Wright United States 19 2.0k 2.2× 563 1.5× 677 2.5× 417 2.2× 191 1.3× 84 2.7k
W. R. Buckland United Kingdom 21 428 0.5× 175 0.5× 207 0.8× 195 1.0× 36 0.2× 62 1.9k
Y. L. Tong United States 16 678 0.8× 248 0.7× 482 1.8× 337 1.8× 142 1.0× 56 1.8k

Countries citing papers authored by John Gurland

Since Specialization
Citations

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

Fields of papers citing papers by John Gurland

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John Gurland. 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 John Gurland. The network helps show where John Gurland may publish in the future.

Co-authorship network of co-authors of John Gurland

This figure shows the co-authorship network connecting the top 25 collaborators of John Gurland. A scholar is included among the top collaborators of John Gurland 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 John Gurland. John Gurland 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.
Gurland, John & Jayaram Sethuraman. (1995). How Pooling Failure Data May Reverse Increasing Failure Rates. Journal of the American Statistical Association. 90(432). 1416–1423. 28 indexed citations
2.
Gurland, John, et al.. (1990). Coping with variance heterogeneity. Communication in Statistics- Theory and Methods. 19(11). 4029–4048. 12 indexed citations
3.
Tripathi, Ram C. & John Gurland. (1986). A unified approach to estimating parameters in some generalized poission distributions. Communication in Statistics- Theory and Methods. 15(3). 1017–1034. 6 indexed citations
4.
Dahiya, Ram C. & John Gurland. (1978). Estimating the parameters of a gamma distribution. Trabajos de Estadistica y de Investigacion Operativa. 29(2). 81–87. 4 indexed citations
5.
Tripathi, Ram C. & John Gurland. (1977). A General Family of Discrete Distributions with Hypergeometric Probabilities. Journal of the Royal Statistical Society Series B (Statistical Methodology). 39(3). 349–356. 25 indexed citations
6.
Mehta, J. S. & John Gurland. (1973). A test for equality of means in the presence of correlation and missing values. Biometrika. 60(1). 211–213. 25 indexed citations
7.
Dahiya, Ram C. & John Gurland. (1972). Goodness of Fit Tests for the Gamma and Exponential Distributions. Technometrics. 14(3). 791–791. 11 indexed citations
8.
Hinz, Paul N. & John Gurland. (1970). A Test of Fit for the Negative Binomial and Other Contagious Distributions. Journal of the American Statistical Association. 65(330). 887–887. 2 indexed citations
9.
Dahiya, Ram C. & John Gurland. (1969). 257. Note: Functions of the Sample Mean and Sample Variance of a Poisson Variate. Biometrics. 25(1). 171–171. 4 indexed citations
10.
Mehta, J. S. & John Gurland. (1969). Testing equality of means in the presence of correlation. Biometrika. 56(1). 119–126. 19 indexed citations
11.
Gurland, John. (1968). Inequalities of Expectations of Random Variables Derived by Monotonicity or Convexity. The American Statistician. 22(2). 26–26. 2 indexed citations
12.
Gurland, John. (1967). The Teacher's Corner: An Inequality Satisfied by the Expectation of the Reciprocal of a Random Variable. The American Statistician. 21(2). 24–25. 15 indexed citations
13.
Gurland, John. (1964). Stochastic models in medicine and biology : proceedings of a symposium conducted by the Mathematics Research Center, United States Army, at the University of Wisconsin, Madison, June 12-14, 1963. University of Wisconsin Press eBooks. 4 indexed citations
14.
Bartlett, M. S. & John Gurland. (1964). Stochastic Models in Medicine and Biology.. Journal of the Royal Statistical Society Series C (Applied Statistics). 13(1). 54–54. 3 indexed citations
15.
Katti, S. K. & John Gurland. (1962). Efficiency of certain methods of estimation for the negative binomial and the Neyman type A distributions. Biometrika. 49(1-2). 215–226. 23 indexed citations
16.
Gurland, John, et al.. (1961). A Class of Distributions Applicable to Accidents. Journal of the American Statistical Association. 56(295). 503–517. 71 indexed citations
17.
Gurland, John, et al.. (1960). Small Sample Behaviour of Certain Tests of the Hypothesis of Equal Means Under Variance Heterogeneity. Biometrika. 47(3/4). 345–345. 8 indexed citations
18.
Dahm, Paul A., et al.. (1959). Field Sampling of Alfalfa for the Estimation of Guthion Residues1. Journal of Economic Entomology. 52(5). 791–798. 3 indexed citations
19.
Gurland, John. (1956). On Wallis' Formula. American Mathematical Monthly. 63(9). 643–643. 25 indexed citations
20.
Barankin, Edward W. & John Gurland. (1951). On asymptotically normal, efficient estimators. University of California Press eBooks. 24 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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