M. Pourahmadi

1.4k total citations
23 papers, 944 citations indexed

About

M. Pourahmadi is a scholar working on Statistics and Probability, Applied Mathematics and Mathematical Physics. According to data from OpenAlex, M. Pourahmadi has authored 23 papers receiving a total of 944 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Statistics and Probability, 8 papers in Applied Mathematics and 4 papers in Mathematical Physics. Recurrent topics in M. Pourahmadi's work include Statistical Methods and Bayesian Inference (5 papers), Statistical Methods and Inference (5 papers) and Statistical and numerical algorithms (3 papers). M. Pourahmadi is often cited by papers focused on Statistical Methods and Bayesian Inference (5 papers), Statistical Methods and Inference (5 papers) and Statistical and numerical algorithms (3 papers). M. Pourahmadi collaborates with scholars based in United States, Taiwan and United Arab Emirates. M. Pourahmadi's co-authors include Michael J. Daniels, Raymond Cheng, A. G. Miamee, Barry C. Arnold, Anton Schίck, Priya Kohli, Tsushung A. Hua and Gholam Reza Emad and has published in prestigious journals such as Journal of the American Statistical Association, Biometrics and Biometrika.

In The Last Decade

M. Pourahmadi

21 papers receiving 902 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
M. Pourahmadi United States 13 592 240 183 119 100 23 944
C. K. Chu Taiwan 15 372 0.6× 176 0.7× 86 0.5× 134 1.1× 80 0.8× 38 897
Brajendra C. Sutradhar Canada 17 707 1.2× 215 0.9× 199 1.1× 101 0.8× 38 0.4× 113 979
Pascal Sarda France 15 1.2k 2.1× 489 2.0× 112 0.6× 150 1.3× 46 0.5× 27 1.7k
Ibrahim A. Ahmad United States 21 1.1k 1.8× 277 1.2× 101 0.6× 152 1.3× 16 0.2× 101 1.5k
José A. Dı́az-Garcı́a Mexico 17 489 0.8× 141 0.6× 48 0.3× 90 0.8× 23 0.2× 71 854
Hengjian Cui China 21 891 1.5× 205 0.9× 55 0.3× 92 0.8× 26 0.3× 82 1.2k
Céline Lévy‐Leduc France 13 267 0.5× 99 0.4× 77 0.4× 121 1.0× 51 0.5× 41 656
Christopher C. Heyde Australia 3 313 0.5× 83 0.3× 76 0.4× 161 1.4× 38 0.4× 3 521
Peide Shi China 11 497 0.8× 145 0.6× 52 0.3× 47 0.4× 35 0.3× 25 690
Graciela Boente Argentina 18 964 1.6× 218 0.9× 55 0.3× 90 0.8× 11 0.1× 86 1.2k

Countries citing papers authored by M. Pourahmadi

Since Specialization
Citations

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

Fields of papers citing papers by M. Pourahmadi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of M. Pourahmadi

This figure shows the co-authorship network connecting the top 25 collaborators of M. Pourahmadi. A scholar is included among the top collaborators of M. Pourahmadi 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 M. Pourahmadi. M. Pourahmadi 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.
Kohli, Priya & M. Pourahmadi. (2014). Some prediction problems for stationary random fields with quarter-plane past. Journal of Multivariate Analysis. 127. 112–125. 5 indexed citations
2.
Pourahmadi, M., et al.. (2012). Gaussian estimation of regression and correlation parameters in longitudinal data. Journal of the Association of Arab Universities for Basic and Applied Sciences. 13(1). 28–34.
3.
Daniels, Michael J. & M. Pourahmadi. (2009). Modeling covariance matrices via partial autocorrelations. Journal of Multivariate Analysis. 100(10). 2352–2363. 58 indexed citations
4.
Pourahmadi, M.. (2007). Cholesky Decompositions and Estimation of A Covariance Matrix: Orthogonality of Variance Correlation Parameters. Biometrika. 94(4). 1006–1013. 63 indexed citations
5.
Pourahmadi, M., et al.. (2003). Multi‐variatetAutoregressions: Innovations, Prediction Variances and Exact Likelihood Equations. Journal of Time Series Analysis. 24(6). 739–754. 21 indexed citations
6.
Pourahmadi, M. & Michael J. Daniels. (2002). Dynamic Conditionally Linear Mixed Models for Longitudinal Data. Biometrics. 58(1). 225–231. 51 indexed citations
7.
Cheng, Raymond, A. G. Miamee, & M. Pourahmadi. (2000). Regularity and Minimality of Infinite Variance Processes. Journal of Theoretical Probability. 13(4). 1115–1122. 9 indexed citations
8.
Pourahmadi, M., et al.. (1999). Regression Models with Time Series Errors. Journal of Time Series Analysis. 20(4). 425–433. 10 indexed citations
9.
Pourahmadi, M.. (1999). Joint mean-covariance models with applications to longitudinal data: unconstrained parameterisation. Biometrika. 86(3). 677–690. 395 indexed citations
10.
Cheng, Raymond, A. G. Miamee, & M. Pourahmadi. (1998). Some extremal problems in $L^p(w)$. Proceedings of the American Mathematical Society. 126(8). 2333–2340. 14 indexed citations
11.
Cheng, Raymond, A. G. Miamee, & M. Pourahmadi. (1998). Some extremal problems in 𝐿^{𝑝}(𝑤). Proceedings of the American Mathematical Society. 126(8). 2333–2340. 12 indexed citations
12.
Pourahmadi, M., et al.. (1998). Nonparametric and Non-Linear Models and Data Mining in time Series: A Case-Study on the Canadian Lynx Data. Journal of the Royal Statistical Society Series C (Applied Statistics). 47(2). 187–201. 26 indexed citations
13.
Pourahmadi, M., et al.. (1997). Prediction with incomplete past and interpolation of missing values. Statistics & Probability Letters. 33(4). 341–346. 13 indexed citations
14.
Pourahmadi, M., et al.. (1996). Estimation of the Generalized Prediction Error Variance of a Multiple Time Series. Journal of the American Statistical Association. 91(433). 294–299. 4 indexed citations
15.
Cheng, Raymond & M. Pourahmadi. (1993). Baxter's inequality and convergence of finite predictors of multivariate stochastic processess. Probability Theory and Related Fields. 95(1). 115–124. 31 indexed citations
16.
Cheng, Raymond & M. Pourahmadi. (1993). The mixing rate of a stationary multivariate process. Journal of Theoretical Probability. 6(3). 603–617. 1 indexed citations
17.
Arnold, Barry C. & M. Pourahmadi. (1988). Conditional characterizations of multivariate distributions. Metrika. 35(1). 99–108. 13 indexed citations
18.
Miamee, A. G. & M. Pourahmadi. (1988). Wold decomposition, prediction and parameterization of stationary processes with infinite variance. Probability Theory and Related Fields. 79(1). 145–164. 21 indexed citations
19.
Pourahmadi, M.. (1987). Some sampling properties of empirical characteristic functions viewed as harmonizable stochastic processes. Journal of Statistical Planning and Inference. 17. 345–359. 3 indexed citations
20.
Hua, Tsushung A. & M. Pourahmadi. (1984). Tables of cumulative distribution functions and percentiles of the standardized stable random variables. Communications in Statistics - Simulation and Computation. 13(5). 571–601. 1 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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