Muhammad Aslam

1.5k total citations
92 papers, 1.0k citations indexed

About

Muhammad Aslam is a scholar working on Statistics and Probability, Public Health, Environmental and Occupational Health and Statistics, Probability and Uncertainty. According to data from OpenAlex, Muhammad Aslam has authored 92 papers receiving a total of 1.0k indexed citations (citations by other indexed papers that have themselves been cited), including 41 papers in Statistics and Probability, 17 papers in Public Health, Environmental and Occupational Health and 16 papers in Statistics, Probability and Uncertainty. Recurrent topics in Muhammad Aslam's work include Advanced Statistical Methods and Models (35 papers), Statistical Methods and Inference (18 papers) and Obesity, Physical Activity, Diet (16 papers). Muhammad Aslam is often cited by papers focused on Advanced Statistical Methods and Models (35 papers), Statistical Methods and Inference (18 papers) and Obesity, Physical Activity, Diet (16 papers). Muhammad Aslam collaborates with scholars based in Pakistan, United States and Saudi Arabia. Muhammad Aslam's co-authors include Saima Altaf, Shakeel Ahmad, Sajid Ali, Muhammad Amin, Muhammad Amanullah, Kamal A. Hanash, Hassan M. Alzahrani, Munir Ahmed, Muhammad Aman Ullah and Alaa Mokhtar and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and ACS Applied Materials & Interfaces.

In The Last Decade

Muhammad Aslam

85 papers receiving 970 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Muhammad Aslam Pakistan 18 307 178 168 133 130 92 1.0k
Hardeo Sahai Puerto Rico 21 262 0.9× 69 0.4× 80 0.5× 48 0.4× 151 1.2× 91 1.6k
Michele Nichols United States 17 366 1.2× 293 1.6× 240 1.4× 36 0.3× 531 4.1× 23 1.6k
M. G. Kenward United Kingdom 15 531 1.7× 57 0.3× 70 0.4× 36 0.3× 105 0.8× 27 1.4k
Nadeem Shafique Butt Saudi Arabia 21 848 2.8× 485 2.7× 70 0.4× 36 0.3× 122 0.9× 120 1.6k
Jun‐mo Nam United States 20 366 1.2× 106 0.6× 43 0.3× 49 0.4× 56 0.4× 55 1.1k
Carl V. Phillips United States 18 122 0.4× 91 0.5× 175 1.0× 22 0.2× 118 0.9× 40 1.0k
Farrokh Habibzadeh Iran 16 52 0.2× 182 1.0× 51 0.3× 68 0.5× 147 1.1× 80 1.2k
Xavier Bry France 10 1.4k 4.4× 138 0.8× 29 0.2× 64 0.5× 65 0.5× 37 2.4k
James T. Wassell United States 18 243 0.8× 103 0.6× 25 0.1× 135 1.0× 93 0.7× 38 1.3k
Chun Pang United Kingdom 14 53 0.2× 298 1.7× 46 0.3× 93 0.7× 217 1.7× 33 1.2k

Countries citing papers authored by Muhammad Aslam

Since Specialization
Citations

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

Fields of papers citing papers by Muhammad Aslam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Muhammad Aslam

This figure shows the co-authorship network connecting the top 25 collaborators of Muhammad Aslam. A scholar is included among the top collaborators of Muhammad Aslam 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 Muhammad Aslam. Muhammad Aslam 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
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3.
Aslam, Muhammad, et al.. (2023). Practicing R for Statistical Computing. 4 indexed citations
4.
Aslam, Muhammad, et al.. (2022). Robust estimation of the distributed lag model with multicollinearity and outliers. Communications in Statistics - Simulation and Computation. 53(8). 3933–3947. 1 indexed citations
5.
Altaf, Saima, et al.. (2022). Modeling and Bayesian Analysis of Time between the Breakdown of Electric Feeders. Modelling and Simulation in Engineering. 2022. 1–13. 2 indexed citations
6.
Altaf, Saima, et al.. (2022). Modeling and analysis of recovery time for the COVID-19 patients: a Bayesian approach. Arab Journal of Basic and Applied Sciences. 30(1). 1–12. 5 indexed citations
7.
Suhail, Muhammad, Sohail Chand, & Muhammad Aslam. (2021). New quantile based ridge M-estimator for linear regression models with multicollinearity and outliers. Communications in Statistics - Simulation and Computation. 52(4). 1417–1434. 15 indexed citations
8.
Aslam, Muhammad, et al.. (2021). The Almon M-estimator for the distributed lag model in the presence of outliers. Communications in Statistics - Simulation and Computation. 52(7). 3273–3285. 3 indexed citations
9.
Aslam, Muhammad, et al.. (2020). Diagnostic Performance of Neck Circumference and Cut-off Values for Identifying Overweight and Obese Pakistani Children: A Receiver Operating Characteristic Analysis. Journal of Clinical Research in Pediatric Endocrinology. 12(4). 366–376. 10 indexed citations
10.
Ahmad, Shakeel & Muhammad Aslam. (2020). Another proposal about the new two-parameter estimator for linear regression model with correlated regressors. Communications in Statistics - Simulation and Computation. 51(6). 3054–3072. 18 indexed citations
11.
Aslam, Muhammad, et al.. (2019). Addressing the distributed lag models with heteroscedastic errors. Communications in Statistics - Simulation and Computation. 50(12). 4464–4482. 7 indexed citations
12.
Mustafa, Ghulam, et al.. (2015). Parental beliefs and practice of spiritual methods for their sick children at a tertiary care hospital of Pakistan- a cross sectional questionnaire study. BMC Complementary and Alternative Medicine. 16(1). 14–14. 7 indexed citations
13.
Ullah, Muhammad Aman, et al.. (2013). Assessing Influence on the Liu Estimates in Linear Regression Models. Communication in Statistics- Theory and Methods. 42(17). 3100–3116. 8 indexed citations
14.
Aslam, Muhammad, et al.. (2012). Primary Postpartum Hemorrhage, Still a Big Challenge in Developing World (Experience in Tertiary care Hospitals, KSA versus Pakistan). Annals of King Edward Medical University. 18(1). 17–17. 3 indexed citations
15.
Ali, Sajid, et al.. (2012). A study of the effect of the loss function on Bayes Estimate, posterior risk and hazard function for Lindley distribution. Applied Mathematical Modelling. 37(8). 6068–6078. 58 indexed citations
16.
Ahmed, Munir, et al.. (2011). Inference under Heteroscedasticity of Unknown Form Using an Adaptive Estimator. Communication in Statistics- Theory and Methods. 40(24). 4431–4457. 10 indexed citations
17.
Muhammad, Faqir, et al.. (2008). Adaptive Estimation of Heteroscedastic Linear Regression Model Using Probability Weighted Moments. Journal of Modern Applied Statistical Methods. 7(2). 501–505. 3 indexed citations
18.
Seyam, Raouf, Nabil K. Bissada, Said Kattan, et al.. (2008). Changing Trends in Presentation, Diagnosis and Management of Renal Angiomyolipoma: Comparison of Sporadic and Tuberous Sclerosis Complex-associated Forms. Urology. 72(5). 1077–1082. 122 indexed citations
19.
Aslam, Muhammad, et al.. (2008). Neonatal Arterial Thrombosis at Birth: Case Report and Literature Review. American Journal of Perinatology. 25(6). 347–352. 14 indexed citations
20.
Aslam, Muhammad, et al.. (2007). Estimating and Forecasting Volatility of Financial Time Series in Pakistan with GARCH-type Models. ˜The œLahore journal of economics. 12(2). 115–149. 5 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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