P. Richard Hahn

2.9k total citations · 2 hit papers
23 papers, 622 citations indexed

About

P. Richard Hahn is a scholar working on Statistics and Probability, Artificial Intelligence and Accounting. According to data from OpenAlex, P. Richard Hahn has authored 23 papers receiving a total of 622 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Statistics and Probability, 12 papers in Artificial Intelligence and 4 papers in Accounting. Recurrent topics in P. Richard Hahn's work include Statistical Methods and Inference (13 papers), Statistical Methods and Bayesian Inference (8 papers) and Gaussian Processes and Bayesian Inference (6 papers). P. Richard Hahn is often cited by papers focused on Statistical Methods and Inference (13 papers), Statistical Methods and Bayesian Inference (8 papers) and Gaussian Processes and Bayesian Inference (6 papers). P. Richard Hahn collaborates with scholars based in United States, Hong Kong and United Kingdom. P. Richard Hahn's co-authors include Carlos M. Carvalho, Jared S. Murray, Shira Hahn, Julie Liss, Visar Berisha, Gautam Dasarathy, Pavan Turaga, Jingyu He, Hedibert F. Lopes and Jundong Li and has published in prestigious journals such as Journal of the American Statistical Association, ACM Computing Surveys and Journal of Business and Economic Statistics.

In The Last Decade

P. Richard Hahn

22 papers receiving 602 citations

Hit Papers

Bayesian Regression Tree ... 2020 2026 2022 2024 2020 2021 50 100 150
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. Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion)
    2020 178 citations P. Richard Hahn, Jared S. Murray et al. Bayesian Analysis profile →
  2. Digital medicine and the curse of dimensionality
    2021 178 citations Visar Berisha, P. Richard Hahn et al. npj Digital Medicine profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
P. Richard Hahn United States 11 257 195 94 50 50 23 622
Shaw‐Hwa Lo United States 16 333 1.3× 189 1.0× 25 0.3× 178 3.6× 43 0.9× 52 969
Huazhen Lin China 12 320 1.2× 105 0.5× 39 0.4× 81 1.6× 25 0.5× 60 540
Xinyuan Song Hong Kong 18 563 2.2× 349 1.8× 92 1.0× 72 1.4× 116 2.3× 106 969
Gonzalo García‐Donato Spain 12 263 1.0× 123 0.6× 96 1.0× 22 0.4× 76 1.5× 25 604
Wang Miao United States 15 366 1.4× 118 0.6× 214 2.3× 10 0.2× 44 0.9× 53 914
Chun Yip Yau Hong Kong 11 200 0.8× 65 0.3× 120 1.3× 21 0.4× 35 0.7× 49 528
Wicher Bergsma United Kingdom 11 267 1.0× 176 0.9× 32 0.3× 25 0.5× 96 1.9× 27 538
Silvia Figini Italy 13 26 0.1× 142 0.7× 97 1.0× 41 0.8× 51 1.0× 53 651

Countries citing papers authored by P. Richard Hahn

Since Specialization
Citations

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

Fields of papers citing papers by P. Richard Hahn

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by P. Richard Hahn. 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 P. Richard Hahn. The network helps show where P. Richard Hahn may publish in the future.

Co-authorship network of co-authors of P. Richard Hahn

This figure shows the co-authorship network connecting the top 25 collaborators of P. Richard Hahn. A scholar is included among the top collaborators of P. Richard Hahn 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 P. Richard Hahn. P. Richard Hahn 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.
Hahn, P. Richard, et al.. (2023). Bayesian decision theory for tree-based adaptive screening tests with an application to youth delinquency. The Annals of Applied Statistics. 17(2).
2.
Berisha, Visar, P. Richard Hahn, Shira Hahn, et al.. (2021). Digital medicine and the curse of dimensionality. npj Digital Medicine. 4(1). 153–153. 178 indexed citations breakdown →
3.
He, Jingyu & P. Richard Hahn. (2021). Stochastic Tree Ensembles for Regularized Nonlinear Regression. Journal of the American Statistical Association. 118(541). 551–570. 12 indexed citations
4.
Guo, Ruocheng, Lu Cheng, Jundong Li, P. Richard Hahn, & Huan Liu. (2020). A Survey of Learning Causality with Data. ACM Computing Surveys. 53(4). 1–37. 39 indexed citations
5.
Hahn, P. Richard, Jared S. Murray, & Carlos M. Carvalho. (2020). Bayesian Regression Tree Models for Causal Inference: Regularization, Confounding, and Heterogeneous Effects (with Discussion). Bayesian Analysis. 15(3). 178 indexed citations breakdown →
6.
Xia, Michelle, P. Richard Hahn, & Paul Gustafson. (2020). A Bayesian mixture of experts approach to covariate misclassification. Canadian Journal of Statistics. 48(4). 731–750. 1 indexed citations
7.
He, Jingyu, et al.. (2019). XBART: Accelerated Bayesian Additive Regression Trees. International Conference on Artificial Intelligence and Statistics. 1130–1138. 2 indexed citations
8.
Hahn, P. Richard, et al.. (2019). Portfolio selection for individual passive investing. Applied Stochastic Models in Business and Industry. 36(1). 124–142. 8 indexed citations
9.
He, Jingyu, et al.. (2018). Accelerated Bayesian Additive Regression Trees.. arXiv (Cornell University). 2 indexed citations
10.
Hahn, P. Richard, Jingyu He, & Hedibert F. Lopes. (2018). Efficient Sampling for Gaussian Linear Regression With Arbitrary Priors. Journal of Computational and Graphical Statistics. 28(1). 142–154. 19 indexed citations
11.
Carvalho, Carlos M., et al.. (2018). Post-Processing Posteriors Over Precision Matrices to Produce Sparse Graph Estimates. Bayesian Analysis. 14(4). 10 indexed citations
12.
Hahn, P. Richard, Ryan R. Martin, & Stephen G. Walker. (2017). On Recursive Bayesian Predictive Distributions. Journal of the American Statistical Association. 113(523). 1085–1093. 19 indexed citations
13.
Hahn, P. Richard, Jared S. Murray, & Ioanna Manolopoulou. (2016). A Bayesian Partial Identification Approach to Inferring the Prevalance of Accounting Misconduct. SSRN Electronic Journal. 1 indexed citations
14.
Hahn, P. Richard, et al.. (2016). Bayesian Regularized Regression for Treatment Effect Estimation from Observational Data. SSRN Electronic Journal. 3 indexed citations
15.
Hahn, P. Richard, et al.. (2016). Variable Selection in Seemingly Unrelated Regressions with Random Predictors. SSRN Electronic Journal. 4 indexed citations
16.
Hahn, P. Richard, et al.. (2016). Sparse Mean-Variance Portfolios: A Penalized Utility Approach. SSRN Electronic Journal. 2 indexed citations
17.
Hahn, P. Richard, Jared S. Murray, & Ioanna Manolopoulou. (2015). A Bayesian Partial Identification Approach to Inferring the Prevalence of Accounting Misconduct. Journal of the American Statistical Association. 111(513). 14–26. 18 indexed citations
18.
Hahn, P. Richard & Carlos M. Carvalho. (2015). Decoupling Shrinkage and Selection in Bayesian Linear Models: A Posterior Summary Perspective. Journal of the American Statistical Association. 110(509). 435–448. 86 indexed citations
19.
Hahn, P. Richard, Carlos M. Carvalho, & Sayan Mukherjee. (2013). Partial Factor Modeling: Predictor-Dependent Shrinkage for Linear Regression. Journal of the American Statistical Association. 108(503). 999–1008. 12 indexed citations
20.
Hahn, P. Richard, Carlos M. Carvalho, & James G. Scott. (2012). A Sparse Factor Analytic Probit Model for Congressional Voting Patterns. Journal of the Royal Statistical Society Series C (Applied Statistics). 61(4). 619–635. 14 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Shaw‐Hwa Lo Breakdown of academic impact, for papers by Huazhen Lin Breakdown of academic impact, for papers by Xinyuan Song Breakdown of academic impact, for papers by Gonzalo García‐Donato Breakdown of academic impact, for papers by Wang Miao Breakdown of academic impact, for papers by Chun Yip Yau Breakdown of academic impact, for papers by Wicher Bergsma Breakdown of academic impact, for papers by Silvia Figini
Rankless by CCL
2026