‎M‎ohammad Arashi

1.9k total citations
163 papers, 1.3k citations indexed

About

‎M‎ohammad Arashi is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, ‎M‎ohammad Arashi has authored 163 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 125 papers in Statistics and Probability, 36 papers in Artificial Intelligence and 30 papers in Statistics, Probability and Uncertainty. Recurrent topics in ‎M‎ohammad Arashi's work include Advanced Statistical Methods and Models (81 papers), Statistical Methods and Inference (61 papers) and Statistical Distribution Estimation and Applications (48 papers) ‎M‎ohammad Arashi is often cited by papers focused on Advanced Statistical Methods and Models (81 papers), Statistical Methods and Inference (61 papers) and Statistical Distribution Estimation and Applications (48 papers) ‎M‎ohammad Arashi collaborates with scholars based in Iran, South Africa and United States ‎M‎ohammad Arashi's co-authors include Mahdi Roozbeh, Andriëtte Bekker, Nor Aishah Hamzah, Mohammad Mahdi Rounaghi, Reza Arabi Belaghi, Mauro Gasparini, Yasin Asar, B. M. Golam Kibria, Bahadır Yüzbaşı and Saralees Nadarajah and has published in prestigious journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.

In The Last Decade

‎M‎ohammad Arashi

146 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
‎M‎ohammad Arashi Iran 19 906 310 135 135 120 163 1.3k
Juan Romo Spain 16 596 0.7× 240 0.8× 254 1.9× 169 1.3× 56 0.5× 58 1.2k
Jana Jurečková Czechia 20 1.3k 1.4× 305 1.0× 157 1.2× 155 1.1× 47 0.4× 85 1.6k
Ibrahim A. Ahmad United States 21 1.1k 1.2× 322 1.0× 277 2.1× 233 1.7× 32 0.3× 101 1.5k
Hengjian Cui China 21 891 1.0× 130 0.4× 205 1.5× 120 0.9× 29 0.2× 82 1.2k
Germán Aneiros Spain 20 795 0.9× 63 0.2× 328 2.4× 190 1.4× 70 0.6× 49 1.2k
Xinyu Zhang China 25 1.1k 1.3× 218 0.7× 177 1.3× 349 2.6× 44 0.4× 117 2.2k
S. Ejaz Ahmed Canada 17 785 0.9× 134 0.4× 156 1.2× 104 0.8× 21 0.2× 159 1.1k
Pascal Sarda France 15 1.2k 1.4× 115 0.4× 489 3.6× 118 0.9× 105 0.9× 27 1.7k
Kristofer Månsson Sweden 19 1.1k 1.2× 499 1.6× 33 0.2× 67 0.5× 206 1.7× 66 1.3k
Gilberto A. Paula Brazil 26 1.6k 1.8× 383 1.2× 344 2.5× 214 1.6× 51 0.4× 92 1.9k

Countries citing papers authored by ‎M‎ohammad Arashi

Since Specialization
Citations

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

Fields of papers citing papers by ‎M‎ohammad Arashi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of ‎M‎ohammad Arashi

This figure shows the co-authorship network connecting the top 25 collaborators of ‎M‎ohammad Arashi. A scholar is included among the top collaborators of ‎M‎ohammad Arashi 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 ‎M‎ohammad Arashi. ‎M‎ohammad Arashi 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.
Bekker, Andriëtte, et al.. (2024). Uncovering a generalised gamma distribution: From shape to interpretation. Results in Applied Mathematics. 22. 100461–100461.
2.
Lukman, Adewale F., et al.. (2024). Robust Negative Binomial Regression via the Kibria–Lukman Strategy: Methodology and Application. Mathematics. 12(18). 2929–2929. 2 indexed citations
3.
Arashi, ‎M‎ohammad, et al.. (2024). Ridge-Type Pretest and Shrinkage Estimation Strategies in Spatial Error Models with an Application to a Real Data Example. Mathematics. 12(3). 390–390. 1 indexed citations
4.
Arashi, ‎M‎ohammad, et al.. (2023). Multicollinearity and Linear Predictor Link Function Problems in Regression Modelling of Longitudinal Data. Mathematics. 11(3). 530–530.
5.
Akram, Muhammad Nauman, et al.. (2022). A new improved Liu estimator for the QSAR model with inverse Gaussian response. Communications in Statistics - Simulation and Computation. 53(4). 1873–1888. 7 indexed citations
6.
Arashi, ‎M‎ohammad & Mohammad Mahdi Rounaghi. (2022). Analysis of market efficiency and fractal feature of NASDAQ stock exchange: Time series modeling and forecasting of stock index using ARMA-GARCH model. SHILAP Revista de lepidopterología. 8(1). 30 indexed citations
7.
Arashi, ‎M‎ohammad, et al.. (2021). A High-Dimensional Counterpart for the Ridge Estimator in Multicollinear Situations. Mathematics. 9(23). 3057–3057. 7 indexed citations
8.
Arashi, ‎M‎ohammad, Mahdi Roozbeh, Nor Aishah Hamzah, & Mauro Gasparini. (2021). Ridge regression and its applications in genetic studies. PLoS ONE. 16(4). e0245376–e0245376. 67 indexed citations
9.
Ferreira, Johan, Andriëtte Bekker, & ‎M‎ohammad Arashi. (2020). Advances in Wishart type modeling for channel capacity. UpSpace Institutional Repository (University of Pretoria). 18. 1 indexed citations
10.
Arashi, ‎M‎ohammad, et al.. (2020). Density derivative estimation for stationary and strongly mixing data. Alexandria Engineering Journal. 59(4). 2323–2330.
11.
Arashi, ‎M‎ohammad, et al.. (2019). Improved estimators for stress-strength reliability using record ranked set sampling scheme. Communications in Statistics - Simulation and Computation. 48(9). 2708–2726. 5 indexed citations
12.
Arashi, ‎M‎ohammad, et al.. (2017). On the ridge regression estimator with sub-space restriction. Communication in Statistics- Theory and Methods. 46(23). 11854–11865. 11 indexed citations
13.
Jenatabadi, Hashem Salarzadeh, et al.. (2017). Testing students’ e-learning via Facebook through Bayesian structural equation modeling. PLoS ONE. 12(9). e0182311–e0182311. 16 indexed citations
14.
Rounaghi, Mohammad Mahdi, et al.. (2015). Stock price forecasting for companies listed on Tehran stock exchange using multivariate adaptive regression splines model and semi-parametric splines technique. Physica A Statistical Mechanics and its Applications. 438. 625–633. 31 indexed citations
15.
Belaghi, Reza Arabi, et al.. (2014). On the Construction of Preliminary Test Estimator Based on Record Values for the Burr XII Model. Communication in Statistics- Theory and Methods. 44(1). 1–23. 24 indexed citations
16.
Arashi, ‎M‎ohammad, et al.. (2014). A NEW DEFINITION OF FORM-INVARIANCE MATRIX VARIATE DISTRIBUTIONS. UpSpace Institutional Repository (University of Pretoria). 48(2). 205–212.
17.
Arashi, ‎M‎ohammad. (2013). ON SELBERG-TYPE SQUARE MATRICES INTEGRALS. SHILAP Revista de lepidopterología. 1 indexed citations
18.
Arashi, ‎M‎ohammad, et al.. (2011). Using improved estimation strategies to combat multicollinearity. Journal of Statistical Computation and Simulation. 81(12). 1773–1797. 22 indexed citations
19.
Rad, A. Habibi, et al.. (2011). Statistical Evidences in Type-II Censored Data. 10(1). 1–12. 1 indexed citations
20.
Arashi, ‎M‎ohammad, et al.. (2011). On Mathematical Characteristics of some Improved Estimators of the Mean and Variance Components in Elliptically Contoured Models. 10(2). 237–266. 2 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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