L. R. Haff

872 total citations
16 papers, 591 citations indexed

About

L. R. Haff is a scholar working on Statistics and Probability, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, L. R. Haff has authored 16 papers receiving a total of 591 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Statistics and Probability, 6 papers in Artificial Intelligence and 2 papers in Computer Vision and Pattern Recognition. Recurrent topics in L. R. Haff's work include Statistical Methods and Bayesian Inference (6 papers), Random Matrices and Applications (6 papers) and Bayesian Methods and Mixture Models (6 papers). L. R. Haff is often cited by papers focused on Statistical Methods and Bayesian Inference (6 papers), Random Matrices and Applications (6 papers) and Bayesian Methods and Mixture Models (6 papers). L. R. Haff collaborates with scholars based in United States. L. R. Haff's co-authors include Michael H. Goldbaum, Mark Nelson, Anirban Dasgupta, Lawrence Brown, William E. Strawderman and James O. Berger and has published in prestigious journals such as Journal of the American Statistical Association, The Annals of Statistics and Journal of Multivariate Analysis.

In The Last Decade

L. R. Haff

15 papers receiving 521 citations

Peers

L. R. Haff
P. L. Davies Germany
Richard C. Liu United States
L.C. Zhao United States
Chunming Zhang United States
Mark G. Low United States
P. L. Davies Germany
L. R. Haff
Citations per year, relative to L. R. Haff L. R. Haff (= 1×) peers P. L. Davies

Countries citing papers authored by L. R. Haff

Since Specialization
Citations

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

Fields of papers citing papers by L. R. Haff

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of L. R. Haff

This figure shows the co-authorship network connecting the top 25 collaborators of L. R. Haff. A scholar is included among the top collaborators of L. R. Haff 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 L. R. Haff. L. R. Haff is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

16 of 16 papers shown
1.
Brown, Lawrence, Anirban Dasgupta, L. R. Haff, & William E. Strawderman. (2006). The heat equation and Stein's identity: Connections, applications. Journal of Statistical Planning and Inference. 136(7). 2254–2278. 20 indexed citations
2.
Dasgupta, Anirban & L. R. Haff. (2005). Asymptotic values and expansions for the correlation between different measures of spread. Journal of Statistical Planning and Inference. 136(7). 2197–2212. 3 indexed citations
3.
Haff, L. R.. (1991). The Variational Form of Certain Bayes Estimators. The Annals of Statistics. 19(3). 77 indexed citations
4.
Goldbaum, Michael H., et al.. (1990). The discrimination of similarly colored objects in computer images of the ocular fundus.. PubMed. 31(4). 617–23. 41 indexed citations
5.
Haff, L. R.. (1986). On linear lon-odds and estimation of discriminant coefficients. Communication in Statistics- Theory and Methods. 15(7). 2131–2144. 10 indexed citations
6.
Haff, L. R., et al.. (1986). The superharmonic condition for simultaneous estimation of means in exponential familles. Canadian Journal of Statistics. 14(1). 43–54. 5 indexed citations
7.
Haff, L. R. & James O. Berger. (1983). A CLASS OF MINIMAX ESTIMATORS OF A NORMAL MEAN VECTOR FOR ARBITRARY QUADRATIC LOSS AND UNKNOWN COVARIANCE MATRIX. Statistics & Risk Modeling. 1(2). 8 indexed citations
9.
Haff, L. R.. (1981). Further identities for the Wishart distribution with applications in regression. Canadian Journal of Statistics. 9(2). 215–224. 14 indexed citations
10.
Haff, L. R.. (1980). Empirical Bayes Estimation of the Multivariate Normal Covariance Matrix. The Annals of Statistics. 8(3). 170 indexed citations
11.
Haff, L. R.. (1979). An identity for the Wishart distribution with applications. Journal of Multivariate Analysis. 9(4). 531–544. 124 indexed citations
12.
Haff, L. R.. (1979). Estimation of the Inverse Covariance Matrix: Random Mixtures of the Inverse Wishart Matrix and the Identity. The Annals of Statistics. 7(6). 65 indexed citations
13.
Haff, L. R.. (1978). The Multivariate Normal Mean with Intraclass Correlated Components: Estimation of Urban Fire Alarm Probabilities. Journal of the American Statistical Association. 73(364). 767–774. 3 indexed citations
14.
Haff, L. R.. (1977). Minimax estimators for a multinormal precision matrix. Journal of Multivariate Analysis. 7(3). 374–385. 47 indexed citations
15.
Haff, L. R.. (1976). Minimax estimators of the multinormal mean: Autoregressive priors. Journal of Multivariate Analysis. 6(2). 265–280. 2 indexed citations
16.
Haff, L. R.. (1973). Bayesian regression with autoregressive priors. 1 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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