G. N. Singh

870 total citations
131 papers, 624 citations indexed

About

G. N. Singh is a scholar working on Statistics and Probability, Artificial Intelligence and Sociology and Political Science. According to data from OpenAlex, G. N. Singh has authored 131 papers receiving a total of 624 indexed citations (citations by other indexed papers that have themselves been cited), including 123 papers in Statistics and Probability, 21 papers in Artificial Intelligence and 10 papers in Sociology and Political Science. Recurrent topics in G. N. Singh's work include Survey Sampling and Estimation Techniques (119 papers), Statistical Methods and Bayesian Inference (39 papers) and Bayesian Methods and Mixture Models (17 papers). G. N. Singh is often cited by papers focused on Survey Sampling and Estimation Techniques (119 papers), Statistical Methods and Bayesian Inference (39 papers) and Bayesian Methods and Mixture Models (17 papers). G. N. Singh collaborates with scholars based in India, Saudi Arabia and United States. G. N. Singh's co-authors include Jong‐Min Kim, Fozia Homa, Sarjinder Singh, Cem Kadılar, H. M. Srivastava, Rajesh K. Pandey, Soma Giri, Amod Kumar, V. N. Jha and Marcin Kozak and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

G. N. Singh

119 papers receiving 591 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
G. N. Singh India 13 569 128 41 27 21 131 624
Tolga Zaman Türkiye 15 560 1.0× 62 0.5× 23 0.6× 20 0.7× 63 3.0× 50 616
Hülya Çıngı Türkiye 13 871 1.5× 90 0.7× 46 1.1× 38 1.4× 57 2.7× 23 915
Nadia Hashim Al-Noor Iraq 12 272 0.5× 24 0.2× 7 0.2× 10 0.4× 64 3.0× 49 334
Usman Shahzad Pakistan 14 508 0.9× 38 0.3× 20 0.5× 14 0.5× 54 2.6× 65 566
Subhash Kumar Yadav India 12 295 0.5× 34 0.3× 24 0.6× 47 1.7× 12 0.6× 86 400
Xinran Li United States 11 279 0.5× 23 0.2× 7 0.2× 16 0.6× 9 0.4× 39 450
Daniel Hlubinka Czechia 9 113 0.2× 53 0.4× 13 0.3× 24 0.9× 49 2.3× 31 257
Pier Francesco Perri Italy 13 484 0.9× 94 0.7× 61 1.5× 40 1.5× 17 0.8× 37 524
Shonosuke Sugasawa Japan 10 132 0.2× 56 0.4× 16 0.4× 16 0.6× 19 0.9× 65 305
Nursel Koyuncu Türkiye 13 569 1.0× 55 0.4× 15 0.4× 18 0.7× 73 3.5× 48 604

Countries citing papers authored by G. N. Singh

Since Specialization
Citations

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

Fields of papers citing papers by G. N. Singh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of G. N. Singh

This figure shows the co-authorship network connecting the top 25 collaborators of G. N. Singh. A scholar is included among the top collaborators of G. N. Singh 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 G. N. Singh. G. N. Singh 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.
Singh, G. N., et al.. (2025). Estimation of Population Mean Using Calibrated Weights in Stratified Random Successive Sampling in Presence of Incomplete Data. Journal of Mathematics. 2025(1). 1 indexed citations
2.
Singh, G. N., et al.. (2021). A general estimation technique of population mean under stratified successive sampling in presence of random scrambled response and non-response. Communications in Statistics - Simulation and Computation. 52(11). 5288–5308. 1 indexed citations
3.
Singh, G. N., et al.. (2020). Calibration estimation of population variance under stratified successive sampling in presence of random non response. Communication in Statistics- Theory and Methods. 50(19). 4487–4509. 13 indexed citations
4.
Singh, G. N., et al.. (2019). Efficient Class of Estimators for Finite Population Mean using Auxiliary Information in Two-Occasion Successive Sampling. Journal of Modern Applied Statistical Methods. 17(2). 7 indexed citations
5.
Singh, G. N., et al.. (2019). Some imputation methods to compensate with non-response for estimation of population mean in two-occasion successive sampling. Communication in Statistics- Theory and Methods. 49(14). 3329–3351. 8 indexed citations
6.
Singh, G. N., et al.. (2019). AN AMELIORATED TWO-STAGE RANDOMIZED RESPONSE MODEL FOR ESTIMATING A RARE STIGMATIZED CHARACTERISTIC USING POISSON DISTRIBUTION. Kuwait Journal of Science. 46(2). 2 indexed citations
7.
Singh, G. N., Amod Kumar, & Gajendra K. Vishwakarma. (2018). Class of Estimators for Effective Estimation of Population Mean in Two-Phase sampling. 19(2). 1–13. 1 indexed citations
8.
Singh, G. N., et al.. (2017). Effective estimation strategy of finite population variance using multi-auxiliary variables in double sampling. Journal of Modern Applied Statistical Methods. 16(1). 158–178. 2 indexed citations
9.
Singh, G. N., et al.. (2017). An Improved Estimation Procedure Using Transformed Auxiliary Variable in Two-Occasions Successive Sampling. 18(2). 79–92. 2 indexed citations
10.
Singh, G. N., et al.. (2017). An Improved Effective Rotation Patterns Using Successive Sampling over Two-Occasions. 28(3). 8–22. 1 indexed citations
11.
Singh, G. N., et al.. (2016). Efficient and Unbiased Estimation Procedure of Population Mean in Two-Phase Sampling. Journal of Modern Applied Statistical Methods. 15(2). 171–186. 2 indexed citations
12.
Singh, G. N., et al.. (2016). An Improved Generalized Estimation Procedure of Current Population Mean in Two-Occasion Successive Sampling. Journal of Modern Applied Statistical Methods. 15(2). 187–206. 1 indexed citations
13.
Singh, G. N., et al.. (2016). Estimation of Population Mean on Recent Occasion under Non-Response in h-Occasion Successive Sampling. Journal of Modern Applied Statistical Methods. 15(2). 149–170.
14.
Singh, G. N., et al.. (2015). Some Improved Estimators for Population Mean in Double Sampling. 26(3). 36–45.
15.
Singh, G. N., et al.. (2014). An Improved Estimation Procedure of Population Mean in Two Phase Sampling. 18(1). 1–10.
16.
Singh, G. N. & Fozia Homa. (2014). An Improved Estimation Procedure in Two-Phase Successive Sampling. International Journal of Applied Mathematics & Statistics. 52(2). 76–85. 1 indexed citations
17.
Singh, G. N., et al.. (2010). Estimation of population mean at current occasion in presence of several varying auxiliary variates in two-occasion successive sampling. Statistics in Transition New Series. 11(1). 105–126. 4 indexed citations
18.
Singh, G. N., et al.. (2009). SEARCH OF EFFECTIVE ROTATION PATTERNS IN PRESENCE OF AUXILIARY INFORMATION IN SUCCESSIVE SAMPLING OVER TWO OCCASIONS. Statistics in Transition New Series. 10(1). 59–73. 8 indexed citations
19.
Singh, G. N., et al.. (2009). Estimation of population mean on current occasion in two-occasion successive sampling. METRON. 87–103. 17 indexed citations
20.
Singh, G. N., et al.. (2004). On The Use of Chain-Type Ratio to Difference Estimator in Successive Sampling. International Journal of Applied Mathematics & Statistics. 5. 41–49. 32 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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