Javid Shabbir

4.7k citations
240 papers · 3.0k indexed · 1 hit paper · h-index 23

Javid Shabbir

216 papers receiving 2.9k citations

Hit Papers

An introduction to statistical learning with applications...8392021202620222024250500750

Peers

Javid Shabbir
Comparison fields: 5 of 189
  • Statistics and Probability 2.0k
  • Statistics, Probability and Uncertainty 108
  • Artificial Intelligence 340
  • Management Science and Operations Research 77
  • Modeling and Simulation 27
Replace Howard D. Bondell with:
Howard D. Bondell United States
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Citations per field
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Howard D. Bondell · 1×
Citations per year

Countries citing papers authored by Javid Shabbir

Since Specialization
Citations

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

Fields of papers citing papers by Javid Shabbir

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Javid Shabbir, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Javid Shabbir Line = papers co-authored together Javid Shabbir links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20251
2 20220
3 20212
4 20214
5 20209
6 20201
7 201822
8 201816
9
An alternative item sum technique for improved estimators of population mean in sensitive surveys
20170
10
Estimators for Population Mean in Adaptive Cluster Sampling
20172
11
Estimation of the Finite Population Mean, using Median based Estimators in Stratified Random Sampling
20151
12 20143
13 20131
14
An Alternative Item Count Technique in Sensitive Surveys
20126
15
On Item Count Technique in Survey Sampling
20102
16
A family of ratio estimators for population mean in extreme ranked set sampling using two auxiliary variables
20107
17 201015
18 20085
19 200763
20 20055

About Javid Shabbir

Javid Shabbir is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Artificial Intelligence, having authored 240 papers that have together received 3.0k indexed citations. Recurring topics across this work include Survey Sampling and Estimation Techniques (207 papers), Statistical Methods and Bayesian Inference (56 papers), Statistical Distribution Estimation and Applications (46 papers), Bayesian Methods and Mixture Models (28 papers), Advanced Statistical Methods and Models (26 papers), HIV, Drug Use, Sexual Risk (15 papers), Advanced Statistical Process Monitoring (11 papers) and Fuzzy Systems and Optimization (9 papers). The work is most often cited by research in Statistics and Probability (2.0k citations), Statistics, Probability and Uncertainty (108 citations) and Artificial Intelligence (340 citations). Javid Shabbir has collaborated with scholars based in Pakistan, United States and Saudi Arabia. Frequent co-authors include Sat Gupta, Fariha Sohil, Abdul Haq, Sohaib Ahmad, Zawar Hussain, Sushil K. Gupta, R Dawson, Alamgir Khalil, Muhammad Aamir and Bal Kishan Dass. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

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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