Tertius de Wet

832 total citations
58 papers, 545 citations indexed

About

Tertius de Wet is a scholar working on Statistics and Probability, Finance and Artificial Intelligence. According to data from OpenAlex, Tertius de Wet has authored 58 papers receiving a total of 545 indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Statistics and Probability, 24 papers in Finance and 9 papers in Artificial Intelligence. Recurrent topics in Tertius de Wet's work include Financial Risk and Volatility Modeling (22 papers), Statistical Distribution Estimation and Applications (19 papers) and Advanced Statistical Methods and Models (16 papers). Tertius de Wet is often cited by papers focused on Financial Risk and Volatility Modeling (22 papers), Statistical Distribution Estimation and Applications (19 papers) and Advanced Statistical Methods and Models (16 papers). Tertius de Wet collaborates with scholars based in South Africa, Belgium and Denmark. Tertius de Wet's co-authors include Yuri Goegebeur, Jan Beirlant, J. H. Venter, Ronald H. Randles, William C. Parr, A. H. Welsh, W. J. Conradie, James Blignaut, Irène Gijbels and M. Ivette Gomes and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and The Annals of Statistics.

In The Last Decade

Tertius de Wet

52 papers receiving 516 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tertius de Wet South Africa	14	343	246	84	69	59	58	545
Eckhard Liebscher Germany	10	309 0.9×	229 0.9×	51 0.6×	125 1.8×	52 0.9×	37	518
José Juan Quesada-Molina Spain	15	252 0.7×	360 1.5×	83 1.0×	70 1.0×	45 0.8×	33	592
Taoufik Bouezmarni Canada	13	270 0.8×	174 0.7×	39 0.5×	151 2.2×	79 1.3×	35	467
Carles M. Cuadras Spain	12	260 0.8×	244 1.0×	36 0.4×	92 1.3×	33 0.6×	22	500
Christopher C. Heyde Australia	3	313 0.9×	161 0.7×	23 0.3×	83 1.2×	76 1.3×	3	521
Sucharita Ghosh Switzerland	11	170 0.5×	273 1.1×	69 0.8×	87 1.3×	219 3.7×	34	548
Jiří Anděl Czechia	11	164 0.5×	166 0.7×	37 0.4×	51 0.7×	117 2.0×	65	482
Yongcheng Qi United States	17	446 1.3×	344 1.4×	64 0.8×	149 2.2×	66 1.1×	77	749
Zhibiao Zhao United States	9	237 0.7×	146 0.6×	27 0.3×	59 0.9×	82 1.4×	25	392

Countries citing papers authored by Tertius de Wet

Since Specialization

Citations

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

Fields of papers citing papers by Tertius de Wet

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tertius de Wet. 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 Tertius de Wet. The network helps show where Tertius de Wet may publish in the future.

Co-authorship network of co-authors of Tertius de Wet

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

All Works

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20 of 20 papers shown

Wet, Tertius de, et al.. (2023). Robust extreme quantile estimation for Pareto-type tails through an exponential regression model. Communications for Statistical Applications and Methods. 30(6). 531–550. 1 indexed citations

Wet, Tertius de, et al.. (2022). A Nearest Neighbor Open-Set Classifier based on Excesses of Distance Ratios. Journal of Computational and Graphical Statistics. 32(1). 319–328. 4 indexed citations

Wet, Tertius de, et al.. (2021). Robust estimation of Pareto-type tail index through an exponential regression model. Communication in Statistics- Theory and Methods. 52(2). 479–498. 4 indexed citations

Wet, Tertius de, et al.. (2018). The bells of the Stellenbosch Moederkerk. SUNScholar (Stellenbosch University). 44(3). 1–19. 1 indexed citations

Wet, Tertius de, et al.. (2016). A simulation comparison of quantile approximation techniques for compound distributions popular in operational risk. The Journal of Operational Risk. 11(1). 23–48. 1 indexed citations

Wet, Tertius de, et al.. (2015). Combining Scenario and Historical Data in the Loss Distribution Approach: A New Procedure that Incorporates Measures of Agreement between Scenarios and Historical Data. SSRN Electronic Journal.

Wet, Tertius de, et al.. (2015). Kernel regression with Weibull-type tails. Annals of the Institute of Statistical Mathematics. 68(5). 1135–1162. 6 indexed citations

Wet, Tertius de, et al.. (2014). Historic bells in Moravian Missions in South Africa's Western Cape. SUNScholar (Stellenbosch University). 59(2). 94–119. 1 indexed citations

Wet, Tertius de, et al.. (2013). Semi-parametric estimation of inequality measures. 47(1). 33–48. 2 indexed citations

10.

Wet, Tertius de, et al.. (2012). Effectiveness of weighting and bootstrap in the estimation of welfare indices under complex sampling : theory and methods. 46(1). 85–114. 1 indexed citations

11.

Goegebeur, Yuri, Jan Beirlant, & Tertius de Wet. (2010). Kernel estimators for the second order parameter in extreme value statistics. Journal of Statistical Planning and Inference. 140(9). 2632–2652. 46 indexed citations

12.

Goegebeur, Yuri, Jan Beirlant, & Tertius de Wet. (2008). LINKING PARETO-TAIL KERNEL GOODNESS-OF-FIT STATISTICS WITH TAIL INDEX AT OPTIMAL THRESHOLD AND SECOND ORDER ESTIMATION. Digital Access to Libraries. 6(1). 51–69. 33 indexed citations

13.

Goegebeur, Yuri, Jan Beirlant, & Tertius de Wet. (2008). Kernel goodness-of-fit statistics for Pareto-type behavior and threshold selection for tail index estimation. University of Southern Denmark Research Portal (University of Southern Denmark). 1 indexed citations

14.

Goegebeur, Yuri, Jan Beirlant, & Tertius de Wet. (2006). Goodness-of-fit testing and Pareto-tail estimation. University of Southern Denmark Research Portal (University of Southern Denmark). 1 indexed citations

15.

Conradie, W. J., et al.. (2005). Exact and asymptotic distributions of LULU smoothers. Journal of Computational and Applied Mathematics. 186(1). 253–267. 7 indexed citations

16.

Beirlant, Jan, Tertius de Wet, & Yuri Goegebeur. (2005). A goodness-of-fit statistic for Pareto-type behaviour. Journal of Computational and Applied Mathematics. 186(1). 99–116. 32 indexed citations

17.

Wet, Tertius de, et al.. (2004). Saddlepoint approximations for the distribution of regression quantiles. 1 indexed citations

18.

Wet, Tertius de. (2002). Goodnes-of-fit tests for location and scale families based on a weighted L2-Wasserstein distance measure. Test. 11(1). 89–107. 10 indexed citations

19.

Wet, Tertius de, et al.. (1986). Bootstrap confidence intervals for regression coefficients when the residuals are dependent. Journal of Statistical Computation and Simulation. 23(4). 317–327. 4 indexed citations

20.

Wet, Tertius de, et al.. (1979). Efficiency and robustness of hogg’s adaptive trimmed means. Communication in Statistics- Theory and Methods. 8(2). 117–128. 19 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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