Ali Laksaci

1.8k citations
99 papers · 1.3k indexed · h-index 20
Topics
Statistical Methods and Inference (89 papers)Advanced Statistical Methods and Models (38 papers)Bayesian Methods and Mixture Models (35 papers)
Journals
SHILAP Revista de lepidopterologíaComputational Statistics & Data AnalysisPeerJ

In The Last Decade

Ali Laksaci

89 papers receiving 1.2k citations

Peers

Ali Laksaci
Comparison fields: 5 of 68
  • Statistics and Probability 1.1k
  • Artificial Intelligence 525
  • Finance 212
  • Control and Systems Engineering 151
  • Economics and Econometrics 123
Replace Hengjian Cui with:
Hengjian Cui China
Germán Aneiros Spain
Yoshihide Kakizawa Japan
Salim Bouzebda France
Alexander Aue United States
Mark G. Low United States
Élisabeth Gassiat France
Xiangrong Yin United States
Aldo Goia Italy
Edit Gombay Canada
Ali Laksaci relative to Hengjian Cui China Hengjian Cui's profile →
Citations per field
00.5×2.6×
Hengjian Cui · 1×
Citations per year

Countries citing papers authored by Ali Laksaci

Since Specialization
Citations

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

Fields of papers citing papers by Ali Laksaci

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ali Laksaci

This figure shows the co-authorship network connecting the top 25 collaborators of Ali Laksaci. A scholar is included among the top collaborators of Ali Laksaci 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 Ali Laksaci. Ali Laksaci 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
#WorkIndexed citations
1 1
2 0
3 1
4 2
5 2
6 1
7 4
8 6
9 4
10 1
11 3
12 5
13 6
14 3
15 4
16 11
17 7
18 15
19 16
20 58

About Ali Laksaci

Ali Laksaci is a scholar working on Statistics and Probability, Finance and Statistics, Probability and Uncertainty, having authored 99 papers that have together received 1.3k indexed citations. Recurring topics across this work include Statistical Methods and Inference (89 papers), Advanced Statistical Methods and Models (38 papers) and Bayesian Methods and Mixture Models (35 papers). The work is most often cited by research in Statistics and Probability (1.1k citations), Finance (212 citations) and Artificial Intelligence (525 citations). Ali Laksaci has collaborated with scholars based in France, Algeria and Saudi Arabia. Frequent co-authors include Philippe Vieu, Frédéric Ferraty, Mustapha Rachdi, Jacques Demongeot, Salim Bouzebda, Ibrahim M. Almanjahie, Elias Ould-Saı̈d, Sophie Dabo‐Niang, Christophe Crambes and Ali Hamié. Their work appears in journals such as SHILAP Revista de lepidopterología, Computational Statistics & Data Analysis and PeerJ.

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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