Yves G. Berger

794 total citations
51 papers, 483 citations indexed

About

Yves G. Berger is a scholar working on Statistics and Probability, Sociology and Political Science and Artificial Intelligence. According to data from OpenAlex, Yves G. Berger has authored 51 papers receiving a total of 483 indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Statistics and Probability, 11 papers in Sociology and Political Science and 10 papers in Artificial Intelligence. Recurrent topics in Yves G. Berger's work include Statistical Methods and Bayesian Inference (33 papers), Statistical Methods and Inference (19 papers) and Survey Sampling and Estimation Techniques (18 papers). Yves G. Berger is often cited by papers focused on Statistical Methods and Bayesian Inference (33 papers), Statistical Methods and Inference (19 papers) and Survey Sampling and Estimation Techniques (18 papers). Yves G. Berger collaborates with scholars based in United Kingdom, Belgium and Canada. Yves G. Berger's co-authors include Rachel L McCrea, Michael King, C. J. Skinner, J. N. K. Rao, Juan Francisco Muñoz Rosas, Tim Goedemé, Yves Tillé, M. Rueda, S. Martínez and Antonio Arcos and has published in prestigious journals such as Biochemical and Biophysical Research Communications, Biometrika and International Journal of Obesity.

In The Last Decade

Yves G. Berger

47 papers receiving 441 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Yves G. Berger United Kingdom	13	312	107	89	75	37	51	483
R. J. A. Little United States	8	162 0.5×	77 0.7×	43 0.5×	51 0.7×	7 0.2×	10	283
Xanthi Pedeli Greece	14	253 0.8×	16 0.1×	65 0.7×	51 0.7×	24 0.6×	22	556
Ralph S. Woodruff United States	8	178 0.6×	58 0.5×	46 0.5×	70 0.9×	50 1.4×	10	497
Angelo Mazza Italy	10	91 0.3×	83 0.8×	92 1.0×	52 0.7×	8 0.2×	26	281
Guillaume Chauvet France	10	142 0.5×	40 0.4×	40 0.4×	38 0.5×	17 0.5×	38	277
Olayan Albalawi Saudi Arabia	10	97 0.3×	54 0.5×	21 0.2×	35 0.5×	19 0.5×	80	326
Terrance D. Savitsky United States	8	49 0.2×	38 0.4×	40 0.4×	38 0.5×	134 3.6×	31	324
Chanmin Kim South Korea	10	85 0.3×	12 0.1×	25 0.3×	32 0.4×	39 1.1×	28	268
Elizabeth A. Stasny United States	12	309 1.0×	73 0.7×	45 0.5×	32 0.4×	4 0.1×	34	499
Márton Ispány Hungary	12	167 0.5×	16 0.1×	62 0.7×	37 0.5×	9 0.2×	31	388

Countries citing papers authored by Yves G. Berger

Since Specialization

Citations

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

Fields of papers citing papers by Yves G. Berger

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Yves G. Berger. 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 Yves G. Berger. The network helps show where Yves G. Berger may publish in the future.

Co-authorship network of co-authors of Yves G. Berger

This figure shows the co-authorship network connecting the top 25 collaborators of Yves G. Berger. A scholar is included among the top collaborators of Yves G. Berger 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 Yves G. Berger. Yves G. Berger 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

Berger, Yves G., et al.. (2023). A Multivariate Regression Estimator of Levels and Change for Surveys Over Time. Journal of Official Statistics. 39(1). 27–44. 1 indexed citations

Berger, Yves G.. (2021). Testing conditional moment restriction models using empirical likelihood. Econometrics Journal. 25(2). 384–403. 1 indexed citations

Berger, Yves G., et al.. (2016). Modelling complex survey data with population level information: an empirical likelihood approach. Biometrika. 103(2). 447–459. 12 indexed citations

Berger, Yves G., et al.. (2016). Variance Estimation of Imputed Estimators of Change for Repeated Rotating Surveys. International Statistical Review. 85(3). 421–438. 2 indexed citations

Berger, Yves G., et al.. (2015). A Simple Variance Estimator of Change for Rotating Repeated Surveys: an Application to The European Union Statistics on Income and Living Conditions Household Surveys. Journal of the Royal Statistical Society Series A (Statistics in Society). 179(1). 251–272. 9 indexed citations

Berger, Yves G., et al.. (2015). Variance estimation of change of poverty based upon the Turkish EU-SILC survey. ePrints Soton (University of Southampton). 2 indexed citations

Berger, Yves G., et al.. (2015). Variance Estimation of Change in Poverty Rates: an Application to the Turkish EU-SILC Survey. Journal of Official Statistics. 31(2). 155–175. 6 indexed citations

Berger, Yves G. & Juan Francisco Muñoz Rosas. (2015). On Estimating Quantiles Using Auxiliary Information. Journal of Official Statistics. 31(1). 101–119. 5 indexed citations

Berger, Yves G.. (2014). Empirical Likelihood Confidence Intervals under the Rao-Hartley-Cochran Sampling Design. ePrints Soton (University of Southampton). 1 indexed citations

10.

Berger, Yves G., et al.. (2012). Standard error estimation and related sampling issues. Biochemical and Biophysical Research Communications. 203(2). 874–80. 4 indexed citations

11.

Berger, Yves G., et al.. (2012). Variance estimation of imputed estimators of change over time from repeated surveys. ePrints Soton (University of Southampton). 1 indexed citations

12.

McCrea, Rachel L, Yves G. Berger, & Michael King. (2011). Body mass index and common mental disorders: exploring the shape of the association and its moderation by age, gender and education. International Journal of Obesity. 36(3). 414–421. 78 indexed citations

13.

Berger, Yves G.. (2008). A note on the asymptotic equivalence of jackknife and linearization variance estimation for the Gini coefficient. Journal of Official Statistics. 24(4). 541–555. 13 indexed citations

14.

Berger, Yves G. & J. N. K. Rao. (2006). Adjusted Jackknife for Imputation under Unequal Probability Sampling Without Replacement. Journal of the Royal Statistical Society Series B (Statistical Methodology). 68(3). 531–547. 14 indexed citations

15.

Berger, Yves G.. (2004). Variance estimation for change: an evaluation based upon the 2000 Finnish labour force survey. ePrints Soton (University of Southampton). 2 indexed citations

16.

Berger, Yves G.. (2004). Variance estimation for measures of change in probability sampling. Canadian Journal of Statistics. 32(4). 451–467. 22 indexed citations

17.

Berger, Yves G.. (2003). A modified Hájek variance estimator for systematic sampling. ePrints Soton (University of Southampton). 4 indexed citations

18.

Berger, Yves G. & C. J. Skinner. (2003). Variance Estimation for a Low Income Proportion. Journal of the Royal Statistical Society Series C (Applied Statistics). 52(4). 457–468. 30 indexed citations

19.

Berger, Yves G.. (1998). Variance estimation using list sequential scheme for unequal probability sampling. ePrints Soton (University of Southampton). 4 indexed citations

20.

Berger, Yves G.. (1996). Asymptotic variance for sequential sampling without replacement with unequal probabilities. ePrints Soton (University of Southampton). 3 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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