Gregory Rice

1.2k total citations
41 papers, 675 citations indexed

About

Gregory Rice is a scholar working on Economics and Econometrics, Finance and Statistics and Probability. According to data from OpenAlex, Gregory Rice has authored 41 papers receiving a total of 675 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Economics and Econometrics, 21 papers in Finance and 17 papers in Statistics and Probability. Recurrent topics in Gregory Rice's work include Financial Risk and Volatility Modeling (21 papers), Statistical Methods and Inference (14 papers) and Complex Systems and Time Series Analysis (13 papers). Gregory Rice is often cited by papers focused on Financial Risk and Volatility Modeling (21 papers), Statistical Methods and Inference (14 papers) and Complex Systems and Time Series Analysis (13 papers). Gregory Rice collaborates with scholars based in Canada, United States and United Kingdom. Gregory Rice's co-authors include Lajos Horváth, Piotr Kokoszka, Alexander Aue, Yuqian Zhao, I. Berkés, Tony S. Wirjanto, Marie Hušková, Han Lin Shang, Zhenya Liu and Shixuan Wang and has published in prestigious journals such as Journal of Clinical Oncology, Journal of Econometrics and Journal of the Royal Statistical Society Series B (Statistical Methodology).

In The Last Decade

Gregory Rice

38 papers receiving 664 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Gregory Rice Canada 14 324 288 272 91 89 41 675
Siegfried Hörmann United States 18 388 1.2× 494 1.7× 405 1.5× 127 1.4× 173 1.9× 42 1.1k
Degui Li United Kingdom 16 433 1.3× 252 0.9× 420 1.5× 235 2.6× 111 1.2× 79 904
Dominik Wied Germany 15 379 1.2× 391 1.4× 195 0.7× 170 1.9× 69 0.8× 72 660
Graciela González–Farías Mexico 12 340 1.0× 201 0.7× 330 1.2× 232 2.5× 112 1.3× 44 878
Robert Stelzer Germany 14 193 0.6× 453 1.6× 131 0.5× 54 0.6× 86 1.0× 33 557
Jens‐Peter Kreiß Germany 15 240 0.7× 469 1.6× 526 1.9× 200 2.2× 78 0.9× 46 969
William P. McCormick United States 16 191 0.6× 435 1.5× 360 1.3× 184 2.0× 188 2.1× 70 833
Wai Keung Li Hong Kong 17 285 0.9× 545 1.9× 409 1.5× 175 1.9× 82 0.9× 40 824
Pavel Čı́žek Netherlands 11 133 0.4× 134 0.5× 183 0.7× 37 0.4× 65 0.7× 50 484
Gabriel Frahm Germany 10 192 0.6× 380 1.3× 145 0.5× 89 1.0× 126 1.4× 36 619

Countries citing papers authored by Gregory Rice

Since Specialization
Citations

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

Fields of papers citing papers by Gregory Rice

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Gregory Rice

This figure shows the co-authorship network connecting the top 25 collaborators of Gregory Rice. A scholar is included among the top collaborators of Gregory Rice 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 Gregory Rice. Gregory Rice 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.
Horváth, Lajos & Gregory Rice. (2024). Change Point Analysis for Time Series. Springer series in statistics. 9 indexed citations
2.
Asselin-Labat, Marie-Liesse, et al.. (2024). Using random forests to uncover the predictive power of distance-varying cell interactions in tumor microenvironments. PLoS Computational Biology. 20(6). e1011361–e1011361. 2 indexed citations
3.
Kim, Mi‐Hyun, Piotr Kokoszka, & Gregory Rice. (2023). White noise testing for functional time series. 17(none). 4 indexed citations
4.
Rice, Gregory, et al.. (2023). Functional spherical autocorrelation: A robust estimate of the autocorrelation of a functional time series. Electronic Journal of Statistics. 17(1). 3 indexed citations
5.
Rice, Gregory, Tony S. Wirjanto, & Yuqian Zhao. (2023). Exploring volatility of crude oil intraday return curves: A functional GARCH-X model. Journal of commodity markets. 32. 100361–100361. 7 indexed citations
6.
Liu, Zhenya, et al.. (2021). Detecting common breaks in the means of high dimensional cross-dependent panels. Econometrics Journal. 25(2). 362–383. 4 indexed citations
7.
Horváth, Lajos, Gregory Rice, & Yuqian Zhao. (2021). Change point analysis of covariance functions: A weighted cumulative sum approach. Journal of Multivariate Analysis. 189. 104877–104877. 11 indexed citations
8.
Rice, Gregory, et al.. (2021). Consistency of binary segmentation for multiple change-point estimation with functional data. Statistics & Probability Letters. 180. 109228–109228. 9 indexed citations
9.
Rice, Gregory, et al.. (2020). Projection pursuit based tests of normality with functional data. Journal of Statistical Planning and Inference. 211. 326–339. 13 indexed citations
10.
Rice, Gregory, et al.. (2020). Functional time series model identification and diagnosis by means of auto- and partial autocorrelation analysis. Computational Statistics & Data Analysis. 155. 107108–107108. 27 indexed citations
11.
Horváth, Lajos, Zhenya Liu, Gregory Rice, & Shixuan Wang. (2019). A functional time series analysis of forward curves derived from commodity futures. International Journal of Forecasting. 36(2). 646–665. 10 indexed citations
12.
Horváth, Lajos & Gregory Rice. (2018). Asymptotics for empirical eigenvalue processes in high-dimensional linear factor models. Journal of Multivariate Analysis. 169. 138–165. 4 indexed citations
13.
Kokoszka, Piotr, Gregory Rice, & Han Lin Shang. (2017). Inference for the autocovariance of a functional time series under conditional heteroscedasticity. Journal of Multivariate Analysis. 162. 32–50. 33 indexed citations
14.
Rice, Gregory, et al.. (2016). A plug-in bandwidth selection procedure for long run covariance estimation with stationary functional time series. ANU Open Research (Australian National University). 35 indexed citations
15.
Horváth, Lajos & Gregory Rice. (2015). An introduction to functional data analysis and a principal component approach for testing the equality of mean curves. Revista Matemática Complutense. 28(3). 505–548. 23 indexed citations
16.
Horváth, Lajos & Gregory Rice. (2014). Rejoinder on: Extensions of some classical methods in change point analysis. Test. 23(2). 287–290. 2 indexed citations
17.
Horváth, Lajos, Marie Hušková, & Gregory Rice. (2013). Test of independence for functional data. Journal of Multivariate Analysis. 117. 100–119. 27 indexed citations
18.
Horváth, Lajos, Piotr Kokoszka, & Gregory Rice. (2013). Testing stationarity of functional time series. Journal of Econometrics. 179(1). 66–82. 133 indexed citations
19.
Berkés, I., Lajos Horváth, & Gregory Rice. (2012). Weak invariance principles for sums of dependent random functions. Stochastic Processes and their Applications. 123(2). 385–403. 42 indexed citations
20.
Rice, Gregory, et al.. (1991). Addressing barriers to perinatal care: a case study of the Access to Maternity Care Committee in Washington State.. PubMed. 106(1). 47–52. 12 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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