Sam J. S. Wu

660 total citations
10 papers, 436 citations indexed

About

Sam J. S. Wu is a scholar working on Statistics, Probability and Uncertainty, Statistics and Probability and Safety, Risk, Reliability and Quality. According to data from OpenAlex, Sam J. S. Wu has authored 10 papers receiving a total of 436 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Statistics, Probability and Uncertainty, 6 papers in Statistics and Probability and 3 papers in Safety, Risk, Reliability and Quality. Recurrent topics in Sam J. S. Wu's work include Probabilistic and Robust Engineering Design (7 papers), Statistical Distribution Estimation and Applications (6 papers) and Hydrology and Drought Analysis (3 papers). Sam J. S. Wu is often cited by papers focused on Probabilistic and Robust Engineering Design (7 papers), Statistical Distribution Estimation and Applications (6 papers) and Hydrology and Drought Analysis (3 papers). Sam J. S. Wu collaborates with scholars based in Taiwan, Canada and Saudi Arabia. Sam J. S. Wu's co-authors include Yao-Ting Sung, N. Balakrishnan, Chien‐Tai Lin, Nandini Kannan, Yao‐Ting Sung, Tak‐Wai Chan and Yu‐Feng Lin and has published in prestigious journals such as Behavior Research Methods, Journal of Statistical Planning and Inference and Journal of Career Assessment.

In The Last Decade

Sam J. S. Wu

9 papers receiving 410 citations

Peers

Sam J. S. Wu

SPU

SURGE

SRRQ

GPC

Basílio de Bragança Pereira Brazil

Nils Blomqvist Sweden

Eileen Wright United Kingdom

Jeffrey Annis United States

Audrey Béliveau Canada

Ingrid A. Amara United States

Yueqin Zhao United States

SBala Bhaskar India

Vasileia Varvarigou United States

Wenzheng Huang United States

Basílio de Bragança Pereira Brazil

Sam J. S. Wu

67 ×0.3

18 ×0.1

SPU

34 ×0.5

SURGE

2 ×0.0

SRRQ

10 ×0.2

GPC

Citations per year, relative to Sam J. S. Wu Sam J. S. Wu (= 1×) peers Basílio de Bragança Pereira

Countries citing papers authored by Sam J. S. Wu

Since Specialization

Citations

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

Fields of papers citing papers by Sam J. S. Wu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sam J. S. Wu. 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 Sam J. S. Wu. The network helps show where Sam J. S. Wu may publish in the future.

Co-authorship network of co-authors of Sam J. S. Wu

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

All Works

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10 of 10 papers shown

Lin, Yu‐Feng, et al.. (2024). Enhancing students’ authentic mathematical problem-solving skills and confidence through error analysis of GPT-4 solutions. Research and Practice in Technology Enhanced Learning. 20. 34–34.

Sung, Yao-Ting & Sam J. S. Wu. (2018). The Visual Analogue Scale for Rating, Ranking and Paired-Comparison (VAS-RRP): A new technique for psychological measurement. Behavior Research Methods. 50(4). 1694–1715. 227 indexed citations

Sung, Yao‐Ting, et al.. (2015). Constructing a Situation-Based Career Interest Assessment for Junior High School Students and Examining Their Interest Structure. Journal of Career Assessment. 24(2). 347–365. 10 indexed citations

Lin, Chien‐Tai, N. Balakrishnan, & Sam J. S. Wu. (2011). Planning Life Tests Based on Progressively Type-I Grouped Censored Data from the Weibull Distribution. Communications in Statistics - Simulation and Computation. 40(4). 574–595. 10 indexed citations

Lin, Chien‐Tai, Sam J. S. Wu, & N. Balakrishnan. (2008). Planning life tests with progressively Type-I interval censored data from the lognormal distribution. Journal of Statistical Planning and Inference. 139(1). 54–61. 28 indexed citations

Lin, Chien‐Tai, Sam J. S. Wu, & N. Balakrishnan. (2006). Monte Carlo Methods for Bayesian Inference on the Linear Hazard Rate Distribution. Communications in Statistics - Simulation and Computation. 35(3). 575–590. 18 indexed citations

Lin, Chien‐Tai, Sam J. S. Wu, & N. Balakrishnan. (2006). Inference for Log-Gamma Distribution Based on Progressively Type-II Censored Data. Communication in Statistics- Theory and Methods. 35(7). 1271–1292. 27 indexed citations

Lin, Chien‐Tai, Sam J. S. Wu, & N. Balakrishnan. (2004). Interval Estimation of Parameters of Log-Gamma Distribution Based on Progressively Censored Data. Communication in Statistics- Theory and Methods. 33(11). 2595–2626. 7 indexed citations

Balakrishnan, N., Nandini Kannan, Chien‐Tai Lin, & Sam J. S. Wu. (2003). Inference for the extreme value distribution under progressive Type-II censoring. Journal of Statistical Computation and Simulation. 74(1). 25–45. 91 indexed citations

10.

Lin, Chien‐Tai, Sam J. S. Wu, & N. Balakrishnan. (2003). Parameter Estimation for the Linear Hazard Rate Distribution Based on Records and Inter-record Times. Communication in Statistics- Theory and Methods. 32(4). 729–748. 18 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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