Siu‐Ming Tam

465 total citations
36 papers, 252 citations indexed

About

Siu‐Ming Tam is a scholar working on Statistics and Probability, Management Science and Operations Research and Artificial Intelligence. According to data from OpenAlex, Siu‐Ming Tam has authored 36 papers receiving a total of 252 indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Statistics and Probability, 11 papers in Management Science and Operations Research and 8 papers in Artificial Intelligence. Recurrent topics in Siu‐Ming Tam's work include Statistical Methods and Bayesian Inference (11 papers), Survey Sampling and Estimation Techniques (10 papers) and demographic modeling and climate adaptation (8 papers). Siu‐Ming Tam is often cited by papers focused on Statistical Methods and Bayesian Inference (11 papers), Survey Sampling and Estimation Techniques (10 papers) and demographic modeling and climate adaptation (8 papers). Siu‐Ming Tam collaborates with scholars based in Australia, United States and Netherlands. Siu‐Ming Tam's co-authors include Jae Kwang Kim, Jaekwang Kim, K. R. W. Brewer, Muhammad Hanif, Raymond L. Chambers, A. H. Welsh, Jens Breckling, Alan H. Dorfman, Jan van den Brakel and Hugh Chipman and has published in prestigious journals such as Journal of the American Statistical Association, Biometrika and The American Statistician.

In The Last Decade

Siu‐Ming Tam

29 papers receiving 214 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Siu‐Ming Tam Australia	9	134	53	46	43	31	36	252
Mauro Scanu Italy	12	211 1.6×	60 1.1×	73 1.6×	156 3.6×	96 3.1×	24	436
Ralf Münnich Germany	10	125 0.9×	54 1.0×	73 1.6×	37 0.9×	89 2.9×	63	287
Vita Ratnasari Indonesia	10	84 0.6×	27 0.5×	80 1.7×	47 1.1×	22 0.7×	91	359
Marcello D’Orazio Italy	9	127 0.9×	59 1.1×	74 1.6×	81 1.9×	62 2.0×	21	346
Márton Ispány Hungary	12	167 1.2×	16 0.3×	37 0.8×	62 1.4×	36 1.2×	31	388
Prayas Sharma India	11	208 1.6×	44 0.8×	17 0.4×	49 1.1×	14 0.5×	48	345
Henry Laniado Colombia	9	31 0.2×	21 0.4×	23 0.5×	17 0.4×	17 0.5×	20	289
Angelo Mazza Italy	10	91 0.7×	83 1.6×	52 1.1×	92 2.1×	37 1.2×	26	281
Shonosuke Sugasawa Japan	10	132 1.0×	16 0.3×	80 1.7×	56 1.3×	54 1.7×	65	305
David Haziza Canada	14	402 3.0×	129 2.4×	77 1.7×	73 1.7×	38 1.2×	48	535

Countries citing papers authored by Siu‐Ming Tam

Since Specialization

Citations

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

Fields of papers citing papers by Siu‐Ming Tam

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Siu‐Ming Tam. 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 Siu‐Ming Tam. The network helps show where Siu‐Ming Tam may publish in the future.

Co-authorship network of co-authors of Siu‐Ming Tam

This figure shows the co-authorship network connecting the top 25 collaborators of Siu‐Ming Tam. A scholar is included among the top collaborators of Siu‐Ming Tam 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 Siu‐Ming Tam. Siu‐Ming Tam 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

Tam, Siu‐Ming, et al.. (2024). A calibrated data‐driven approach for small area estimation using big data. Australian & New Zealand Journal of Statistics. 66(2). 125–145.

Tam, Siu‐Ming, et al.. (2023). A Note on the Optimum Allocation of Resources to Follow up Unit Nonrespondents in Probability Surveys. Journal of Official Statistics. 39(3). 421–433.

Tam, Siu‐Ming. (2021). On a disclosure probability statement for the 5 safes framework. Statistical Journal of the IAOS. 37(2). 693–698. 1 indexed citations

Brakel, Jan van den, et al.. (2020). Measuring Discontinuities in Time Series Obtained with Repeated Sample Surveys. International Statistical Review. 88(1). 155–175. 7 indexed citations

Tam, Siu‐Ming, et al.. (2020). The five V’s, seven virtues and ten rules of big data engagement for official statistics. Statistical Journal of the IAOS. 36(2). 423–433. 6 indexed citations

Kim, Jae Kwang & Siu‐Ming Tam. (2020). Data Integration by Combining Big Data and Survey Sample Data for Finite Population Inference. International Statistical Review. 89(2). 382–401. 25 indexed citations

Tam, Siu‐Ming, et al.. (2015). Big Data, Official Statistics and Some Initiatives by the Australian Bureau of Statistics. International Statistical Review. 83(3). 436–448. 44 indexed citations

Tam, Siu‐Ming, et al.. (2013). Building expertise in mathematical statistics within the Australian bureau of statistics through partnerships with academics.

Tam, Siu‐Ming. (2008). Informing the nation – open access to statistical information in Australia. Statistical Journal of the IAOS. 25(3-4). 145–153. 1 indexed citations

10.

Tam, Siu‐Ming, et al.. (2007). Data communication – Emerging international trends and practices of the Australian Bureau of Statistics. Statistical Journal of the United Nations Economic Commission for Europe. 23(4). 229–247. 2 indexed citations

11.

Tam, Siu‐Ming. (1995). Optimal and Robust Strategies for Cluster Sampling. Journal of the American Statistical Association. 90(429). 379–382. 5 indexed citations

12.

Brewer, K. R. W., Muhammad Hanif, & Siu‐Ming Tam. (1988). How Nearly Can Model-Based Prediction and Design-Based Estimation Be Reconciled?. Journal of the American Statistical Association. 83(401). 128–132. 17 indexed citations

13.

Tam, Siu‐Ming. (1987). Analysis of Repeated Surveys Using a Dynamic Linear Model. International Statistical Review. 55(1). 63–63. 19 indexed citations

14.

Tam, Siu‐Ming. (1987). Optimality of Royall's predictor under a Gaussian superpopulation model. Biometrika. 74(3). 659–660. 2 indexed citations

15.

Tam, Siu‐Ming. (1986). Optimal Prediction in Stochastic Regression Models with Application to the Analysis of Repeated Surveys. Australian Journal of Statistics. 28(3). 345–353. 2 indexed citations

16.

Tam, Siu‐Ming. (1985). On Covariance in Finite Population Sampling. Journal of the Royal Statistical Society Series D (The Statistician). 34(4). 429–429. 2 indexed citations

17.

Tam, Siu‐Ming. (1984). On Covariances from Overlapping Samples. The American Statistician. 38(4). 288–289. 18 indexed citations

18.

Tam, Siu‐Ming, et al.. (1984). Screening of Probability Samples. International Statistical Review. 52(3). 301–301. 3 indexed citations

19.

Tam, Siu‐Ming. (1984). Optimal estimation in survey sampling under a regression superpopulation model. Biometrika. 71(3). 645–647. 8 indexed citations

20.

Tam, Siu‐Ming. (1982). Postcensal Estimates for Local Areas Using Current Samples with Census as the Source of Sampling Frame. International Statistical Review. 50(2). 125–125.

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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