Anoop Kumar

1.0k total citations
92 papers, 652 citations indexed

About

Anoop Kumar is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence. According to data from OpenAlex, Anoop Kumar has authored 92 papers receiving a total of 652 indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Statistics and Probability, 13 papers in Statistics, Probability and Uncertainty and 8 papers in Artificial Intelligence. Recurrent topics in Anoop Kumar's work include Survey Sampling and Estimation Techniques (57 papers), Statistical Distribution Estimation and Applications (38 papers) and Statistical Methods and Bayesian Inference (30 papers). Anoop Kumar is often cited by papers focused on Survey Sampling and Estimation Techniques (57 papers), Statistical Distribution Estimation and Applications (38 papers) and Statistical Methods and Bayesian Inference (30 papers). Anoop Kumar collaborates with scholars based in India, Saudi Arabia and Egypt. Anoop Kumar's co-authors include Shashi Bhushan, Showkat Ahmad Lone, Nithya Jagannathan, Tolga Zaman, Anuja Natesan, Priya Premkumar, Yusra Tashkandy, Amer Ibrahim Al‐Omari, M. E. Bakr and Usman Shahzad and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

Anoop Kumar

77 papers receiving 619 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Anoop Kumar India 14 480 63 62 38 32 92 652
C. Y. Wang United States 12 510 1.1× 16 0.3× 85 1.4× 8 0.2× 48 1.5× 15 681
Ricardo Puziol de Oliveira Brazil 8 180 0.4× 74 1.2× 31 0.5× 1 0.0× 38 1.2× 42 407
Abdulaziz S. Alghamdi Saudi Arabia 13 246 0.5× 102 1.6× 49 0.8× 9 0.2× 47 383
Wenqing He Canada 13 219 0.5× 16 0.3× 83 1.3× 19 0.5× 66 631
Paul Zhang United States 11 66 0.1× 12 0.2× 40 0.6× 20 0.5× 1 0.0× 19 525
Ignacio López‐de‐Ullibarri Spain 11 77 0.2× 21 0.3× 42 0.7× 3 0.1× 30 333
Amandeep Singh India 9 7 0.0× 22 0.3× 46 0.7× 11 0.3× 21 0.7× 36 360
Sergej Potapov Germany 13 52 0.1× 2 0.0× 26 0.4× 12 0.3× 3 0.1× 21 534
Andrew R. Miller United States 8 55 0.1× 9 0.1× 17 0.3× 20 0.5× 12 769
Tianxi Cai United States 8 77 0.2× 4 0.1× 31 0.5× 2 0.1× 2 0.1× 17 292

Countries citing papers authored by Anoop Kumar

Since Specialization
Citations

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

Fields of papers citing papers by Anoop Kumar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Anoop Kumar

This figure shows the co-authorship network connecting the top 25 collaborators of Anoop Kumar. A scholar is included among the top collaborators of Anoop Kumar 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 Anoop Kumar. Anoop Kumar 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.
Bhushan, Shashi & Anoop Kumar. (2025). Robust Difference and Ratio Type Estimators in Presence of Correlated Measurement Errors Under Ranked Set Sampling. Calcutta Statistical Association Bulletin. 77(2). 192–224.
2.
Ding, Dan, et al.. (2024). A novel probabilistic model with properties: Its implementation to the vocal music and reliability products. Alexandria Engineering Journal. 107. 254–267. 1 indexed citations
3.
Kumar, Anoop, et al.. (2024). Efficient imputation methods in case of measurement errors. Heliyon. 10(6). e26864–e26864. 3 indexed citations
4.
Kumar, Anoop, et al.. (2024). On some robust imputation methods in presence of correlated measurement errors with real data applications. Alexandria Engineering Journal. 104. 136–149. 3 indexed citations
5.
Kumar, Anoop, et al.. (2024). Novel imputation methods under stratified simple random sampling. Alexandria Engineering Journal. 95. 236–246. 7 indexed citations
6.
Bhushan, Shashi, et al.. (2023). On classes of robust estimators in presence of correlated measurement errors. Measurement. 220. 113383–113383. 7 indexed citations
7.
Bhushan, Shashi & Anoop Kumar. (2023). New efficient class of estimators of population mean using two-phase sampling. International Journal of Mathematics in Operational Research. 24(2). 155–155. 1 indexed citations
8.
Bhushan, Shashi, et al.. (2023). On stratified ranked set sampling for the quest of an optimal class of estimators. Alexandria Engineering Journal. 86. 79–97. 4 indexed citations
9.
Bhushan, Shashi & Anoop Kumar. (2023). Imputation of missing data using multi auxiliary information under ranked set sampling. Communications in Statistics - Simulation and Computation. 54(5). 1500–1521. 17 indexed citations
10.
Bhushan, Shashi, et al.. (2023). Performance evaluation of novel logarithmic estimators under correlated measurement errors. Communication in Statistics- Theory and Methods. 53(15). 5353–5363. 6 indexed citations
11.
Bhushan, Shashi, et al.. (2023). An Efficient Class of Estimators in Stratified Random Sampling with an Application to Real Data. Axioms. 12(6). 576–576. 12 indexed citations
12.
Bhushan, Shashi, et al.. (2023). Efficient Difference and Ratio-Type Imputation Methods under Ranked Set Sampling. Axioms. 12(6). 558–558. 17 indexed citations
13.
Bhushan, Shashi & Anoop Kumar. (2023). On some efficient classes of estimators using auxiliary attribute. Statistics in Transition New Series. 24(2). 141–157. 2 indexed citations
14.
Bhushan, Shashi, et al.. (2023). Mean Estimation for Time-Based Surveys Using Memory-Type Logarithmic Estimators. Mathematics. 11(9). 2125–2125. 13 indexed citations
15.
Bhushan, Shashi, et al.. (2023). Some Optimal Classes of Estimators Based on Multi-Auxiliary Information. Axioms. 12(6). 515–515. 5 indexed citations
16.
Bhushan, Shashi, et al.. (2022). Estimation of population mean in presence of missing data under simple random sampling. Communications in Statistics - Simulation and Computation. 52(12). 6048–6069. 23 indexed citations
17.
Bhushan, Shashi, et al.. (2022). Some Improved Classes of Estimators in Stratified Sampling Using Bivariate Auxiliary Information. SHILAP Revista de lepidopterología. 2022. 1–23. 6 indexed citations
18.
Bhushan, Shashi, et al.. (2022). Modified Class of Estimators Using Ranked Set Sampling. Mathematics. 10(21). 3921–3921. 6 indexed citations
19.
Bhushan, Shashi, et al.. (2022). Evaluating the performance of memory type logarithmic estimators using simple random sampling. PLoS ONE. 17(12). e0278264–e0278264. 13 indexed citations
20.
Bhushan, Shashi, et al.. (2022). On Efficient Estimation of the Population Mean under Stratified Ranked Set Sampling. Journal of Mathematics. 2022(1). 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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