Sharad D. Gore

507 total citations
33 papers, 289 citations indexed

About

Sharad D. Gore is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Computer Networks and Communications. According to data from OpenAlex, Sharad D. Gore has authored 33 papers receiving a total of 289 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Statistics and Probability, 6 papers in Statistics, Probability and Uncertainty and 5 papers in Computer Networks and Communications. Recurrent topics in Sharad D. Gore's work include Advanced Statistical Methods and Models (9 papers), Advanced Statistical Process Monitoring (4 papers) and Spectroscopy and Chemometric Analyses (4 papers). Sharad D. Gore is often cited by papers focused on Advanced Statistical Methods and Models (9 papers), Advanced Statistical Process Monitoring (4 papers) and Spectroscopy and Chemometric Analyses (4 papers). Sharad D. Gore collaborates with scholars based in India, United States and Iran. Sharad D. Gore's co-authors include G. P. Patil, T. V. Ramanathan, Gianfranco Lovison, Anil Patwardhan, Masoud Masoudi, Balu A. Chopade, Dilip D. Dhavale, C. Taillie, Chittaranjan S. Yajnik and Morteza Abdullatif Khafaie and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Environmental Science and Pollution Research.

In The Last Decade

Sharad D. Gore

32 papers receiving 260 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sharad D. Gore India 9 98 44 36 34 32 33 289
Omar Ruíz-Barzola Ecuador 11 47 0.5× 57 1.3× 25 0.7× 57 1.7× 3 0.1× 48 294
Christer Albano Sweden 10 27 0.3× 30 0.7× 17 0.5× 18 0.5× 13 0.4× 15 397
Γεώργιος Παπαδόπουλος Greece 14 53 0.5× 29 0.7× 12 0.3× 117 3.4× 4 0.1× 45 492
Guanqun Cao United States 12 177 1.8× 20 0.5× 4 0.1× 15 0.4× 22 0.7× 36 437
Raúl Martín Martín Spain 11 21 0.2× 31 0.7× 49 1.4× 24 0.7× 3 0.1× 38 406
Marvin Lentner United States 9 44 0.4× 35 0.8× 3 0.1× 48 1.4× 21 0.7× 21 319
Sílvio Sandoval Zocchi Brazil 9 99 1.0× 22 0.5× 3 0.1× 47 1.4× 16 0.5× 22 284
Weixing Song United States 11 224 2.3× 43 1.0× 3 0.1× 33 1.0× 3 0.1× 51 419
Yue Niu United States 10 111 1.1× 23 0.5× 5 0.1× 34 1.0× 24 413
Saeid Tahmasebi Iran 13 362 3.7× 199 4.5× 62 1.7× 12 0.4× 66 658

Countries citing papers authored by Sharad D. Gore

Since Specialization
Citations

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

Fields of papers citing papers by Sharad D. Gore

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sharad D. Gore. 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 Sharad D. Gore. The network helps show where Sharad D. Gore may publish in the future.

Co-authorship network of co-authors of Sharad D. Gore

This figure shows the co-authorship network connecting the top 25 collaborators of Sharad D. Gore. A scholar is included among the top collaborators of Sharad D. Gore 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 Sharad D. Gore. Sharad D. Gore 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.
Gore, Sharad D., et al.. (2020). Classification of Categorical Outcome Variable Based on Logistic Regression and Tree Algorithm. International Journal of Recent Technology and Engineering (IJRTE). 8(5). 4685–4690. 1 indexed citations
2.
Gore, Sharad D., et al.. (2020). A Comparative Study of Linear Regression and Regression Tree. SSRN Electronic Journal. 2 indexed citations
3.
Gore, Sharad D., et al.. (2018). A hybrid part-of-speech tagger for Marathi sentences. 1–10. 2 indexed citations
4.
Khafaie, Morteza Abdullatif, et al.. (2017). Air pollution and respiratory health among diabetic and non-diabetic subjects in Pune, India—results from the Wellcome Trust Genetic Study. Environmental Science and Pollution Research. 24(18). 15538–15546. 21 indexed citations
5.
Khafaie, Morteza Abdullatif, et al.. (2017). Particulate matter and markers of glycemic control and insulin resistance in type 2 diabetic patients: result from Wellcome Trust Genetic study. Journal of Exposure Science & Environmental Epidemiology. 28(4). 328–336. 19 indexed citations
6.
Ramanathan, T. V., et al.. (2014). THE EFFICIENCY OF MODIFIED JACKKNIFE AND RIDGE TYPE REGRESSION ESTIMATORS: A COMPARISON. SHILAP Revista de lepidopterología. 40 indexed citations
7.
Gore, Sharad D., et al.. (2012). Anomaly detection algorithm using multiagents. International journal of scientific and technology research. 1(3). 54–57. 1 indexed citations
8.
Gore, Sharad D., et al.. (2011). Intrusion Detection System (IDS) &Intrusion Prevention System (IPS): Case Study. 4 indexed citations
9.
Patil, Ganapati P., Sharad D. Gore, & C. Taillie. (2010). Composite Sampling. 4 indexed citations
10.
Gore, Sharad D., et al.. (2010). Use of post-stratification in composite sampling for estimating mean. Environmental and Ecological Statistics. 18(3). 535–542.
11.
Patil, Ganapati P., Sharad D. Gore, & C. Taillie. (2010). Composite Sampling: A Novel Method to Accomplish Observational Economy in Environmental Studies. Digital Access to Libraries (Université catholique de Louvain (UCL), l'Université de Namur (UNamur) and the Université Saint-Louis (USL-B)). 12 indexed citations
12.
Özkale, M. Revan, et al.. (2009). Combining Unbiased Ridge and Principal Component Regression Estimators. Communication in Statistics- Theory and Methods. 38(13). 2201–2209. 20 indexed citations
13.
Gore, Sharad D., et al.. (2009). Two Strategies for Removing Multicollinearity. 3. 62–79. 1 indexed citations
14.
Ramanathan, T. V., et al.. (2009). On the distribution of shrinkage parameters of Liu-type estimators. Brazilian Journal of Probability and Statistics. 23(1). 4 indexed citations
15.
Gore, Sharad D., et al.. (2009). RIDGE REGRESSION ESTIMATOR: COMBINING UNBIASED AND ORDINARY RIDGE REGRESSION METHODS OF ESTIMATION. 7 indexed citations
16.
Gore, Sharad D., et al.. (2008). A new estimator in multiple linear regression model. Model Assisted Statistics and Applications. 3(3). 187–200. 6 indexed citations
17.
Gore, Sharad D., et al.. (2008). Effect of jackknifing on various ridge type estimators. Model Assisted Statistics and Applications. 3(3). 201–210. 8 indexed citations
18.
Gore, Sharad D.. (2008). Sampling for Natural Resource Monitoring. Journal of the American Statistical Association. 103(482). 889–890. 1 indexed citations
19.
Gore, Sharad D., et al.. (2002). Isolation, Characterization, and Plasmid pUPI126-Mediated Indole-3-Acetic Acid Production in Acinetobacter Strains from Rhizosphere of Wheat. Applied Biochemistry and Biotechnology. 102-103(1-6). 21–40. 49 indexed citations
20.
Gore, Sharad D. & G. P. Patil. (1994). Identifying extremely large values using composite sample data. Environmental and Ecological Statistics. 1(3). 227–245. 6 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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