Richard Huggins

5.1k total citations · 1 hit paper
136 papers, 3.8k citations indexed

About

Richard Huggins is a scholar working on Statistics and Probability, Genetics and Ecology. According to data from OpenAlex, Richard Huggins has authored 136 papers receiving a total of 3.8k indexed citations (citations by other indexed papers that have themselves been cited), including 75 papers in Statistics and Probability, 38 papers in Genetics and 27 papers in Ecology. Recurrent topics in Richard Huggins's work include Census and Population Estimation (41 papers), Genetics and Neurodevelopmental Disorders (25 papers) and Statistical Methods and Inference (24 papers). Richard Huggins is often cited by papers focused on Census and Population Estimation (41 papers), Genetics and Neurodevelopmental Disorders (25 papers) and Statistical Methods and Inference (24 papers). Richard Huggins collaborates with scholars based in Australia, Taiwan and United States. Richard Huggins's co-authors include Danuta Z. Loesch, Minh Bui, Randi J. Hagerman, Annette K. Taylor, Cheryl Dissanayake, Sally Clifford, I. V. Basawa, Jakub Stoklosa, Robert G. Staudte and Paul S. F. Yip and has published in prestigious journals such as Journal of the American Statistical Association, Neurology and Annals of Neurology.

In The Last Decade

Richard Huggins

133 papers receiving 3.6k citations

Hit Papers

On the statistical analysis of capture experiments 1989 2026 2001 2013 1989 100 200 300 400 500

Peers

Richard Huggins
Nelson B. Freimer United States
Janet S. Sinsheimer United States
Andrew S. Allen United States
Dmitri V. Zaykin United States
Daniel E. Weeks United States
Shashaank Vattikuti United States
Christopher Chang United States
Susan E. Hodge United States
A D Carothers United Kingdom
Nelson B. Freimer United States
Richard Huggins
Citations per year, relative to Richard Huggins Richard Huggins (= 1×) peers Nelson B. Freimer

Countries citing papers authored by Richard Huggins

Since Specialization
Citations

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

Fields of papers citing papers by Richard Huggins

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Richard Huggins

This figure shows the co-authorship network connecting the top 25 collaborators of Richard Huggins. A scholar is included among the top collaborators of Richard Huggins 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 Richard Huggins. Richard Huggins 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.
Bugeja, Lyndal, et al.. (2023). Suspension-associated dislocation of the jaw in hanging. International Journal of Legal Medicine. 137(5). 1489–1495. 3 indexed citations
2.
Petrovski, Slavé, Annie Roten, H. R. Miller, et al.. (2014). Validation of a multigenic model to predict seizure control in newly treated epilepsy. Epilepsy Research. 108(10). 1797–1805. 17 indexed citations
3.
Huggins, Richard. (2013). Using speeding detections and numbers of fatalities to estimate relative risk of a fatality for motorcyclists and car drivers. Accident Analysis & Prevention. 59. 296–300. 9 indexed citations
4.
Loesch, Danuta Z., David E. Godler, Mahmoud Shekari Khaniani, et al.. (2009). Linking the FMR1 alleles with small CGG expansions with neurodevelopmental disorders: Preliminary data suggest an involvement of epigenetic mechanisms. American Journal of Medical Genetics Part A. 149A(10). 2306–2310. 22 indexed citations
5.
Dissanayake, Cheryl, et al.. (2008). Behavioural and cognitive phenotypes in idiopathic autism versus autism associated with fragile X syndrome. Journal of Child Psychology and Psychiatry. 50(3). 290–299. 33 indexed citations
6.
Loesch, Danuta Z., et al.. (2006). Transcript levels of the intermediate size or grey zone fragile X mental retardation 1 alleles are raised, and correlate with the number of CGG repeats. Journal of Medical Genetics. 44(3). 200–204. 70 indexed citations
7.
Loesch, Danuta Z., Minh Bui, Wendy Kelso, et al.. (2005). Effect of Turner's syndrome and X-linked imprinting on cognitive status: analysis based on pedigree data. Brain and Development. 27(7). 494–503. 37 indexed citations
8.
Yang, Hsin‐Chou, et al.. (2003). Estimation of the Size of an Open Population Using Local Estimating Equations II: A Partially Parametric Approach. Biometrics. 59(2). 365–374. 5 indexed citations
9.
Huggins, Richard & Anne Chao. (2002). ASYMPTOTIC PROPERTIES OF AN OPTIMAL ESTIMATING FUNCTION APPROACH TO THE ANALYSIS OF MARK RECAPTURE DATA. Communication in Statistics- Theory and Methods. 31(4). 575–595. 5 indexed citations
10.
Loesch, Danuta Z., Richard Huggins, Minh Bui, Annette K. Taylor, & Randi J. Hagerman. (2002). Relationship of deficits of FMR1 gene specific protein with physical phenotype of fragile X males and females in pedigrees: A new perspective. American Journal of Medical Genetics Part A. 118A(2). 127–134. 36 indexed citations
11.
Huggins, Richard & Paul S. F. Yip. (2001). A NOTE ON NONPARAMETRIC INFERENCE FOR CAPTURE-RECAPTURE EXPERIMENTS WITH HETEROGENEOUS CAPTURE PROBABILITIES. Statistica Sinica. 11(3). 13 indexed citations
12.
Loesch, Danuta Z., et al.. (2000). Secular trend in body height and weight of Australian children and adolescents. American Journal of Physical Anthropology. 111(4). 545–556. 74 indexed citations
13.
Huggins, Richard. (2000). Local Estimation of Age‐Dependent Variance Components from Longitudinal Twin Data. Biometrics. 56(2). 537–545. 1 indexed citations
14.
Huggins, Richard. (1996). On the identifiability of measurement error in the bifurcating autoregressive model. Statistics & Probability Letters. 27(1). 17–23. 6 indexed citations
15.
Loesch, Danuta Z., Richard Huggins, Vida Petrovic, & HR Slater. (1995). Expansion of the CGG repeat in fragile X in the FMR1 gene depends on the sex of the offspring.. PubMed. 57(6). 1408–13. 24 indexed citations
16.
Huggins, Richard. (1995). A law of large numbers for the bifurcating autoregressive process. Communications in Statistics Stochastic Models. 11(2). 273–278. 6 indexed citations
17.
Loesch, Danuta Z., Richard Huggins, & Ngoc Hoang. (1995). Growth in stature in fragile X families: A mixed longitudinal study. American Journal of Medical Genetics. 58(3). 249–256. 36 indexed citations
18.
Hurley, S F, et al.. (1994). Recruitment activities and sociodemographic factors that predict attendance at a mammographic screening program.. American Journal of Public Health. 84(10). 1655–1658. 38 indexed citations
19.
Huggins, Richard. (1992). Fixed accuracy estimation for chain binomial models. Stochastic Processes and their Applications. 41(2). 273–280.
20.
Huggins, Richard & Ian C. Marschner. (1991). ROBUST ANALYSIS OF THE BIFURCATING AUTOREGRESSIVE MODEL IN CELL LINEAGE STUDIES. Australian Journal of Statistics. 33(2). 209–220. 13 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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