Plamen Neytchev
- Statistics and Probability top 5%
- Global and Planetary Change
- Artificial Intelligence
- Atmospheric Science
- Statistics, Probability and Uncertainty top 5%
- Co-authors
- Neyko NeykovPeter FilzmoserRositsa B. DimovaPieter van GelderValentin TodorovJohn de RondeWalter ZucchiniPierre Bénard
- Topics
- Advanced Statistical Methods and Models (7 papers)Climate variability and models (5 papers)Statistical Methods and Bayesian Inference (3 papers)
- Cited by
- Statistics and ProbabilityStatistics, Probability and UncertaintyGlobal and Planetary Change
- Partner nations
- BulgariaAustriaNetherlands
In The Last Decade
Plamen Neytchev
15 papers receiving 268 citations
Peers
Comparison fields: 5 of 62
- Statistics and Probability 122
- Global and Planetary Change 89
- Artificial Intelligence 81
- Atmospheric Science 51
- Statistics, Probability and Uncertainty 36
Countries citing papers authored by Plamen Neytchev
This map shows the geographic impact of Plamen Neytchev'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 Plamen Neytchev with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Plamen Neytchev more than expected).
Fields of papers citing papers by Plamen Neytchev
This network shows the impact of papers produced by Plamen Neytchev. 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 Plamen Neytchev. The network helps show where Plamen Neytchev may publish in the future.
Co-authorship network of co-authors of Plamen Neytchev
This figure shows the co-authorship network connecting the top 25 collaborators of Plamen Neytchev. A scholar is included among the top collaborators of Plamen Neytchev 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 Plamen Neytchev. Plamen Neytchev is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 10 | |
| 2 | 11 | |
| 3 | 12 | |
| 4 | 11 | |
| 5 | 12 | |
| 6 | 8 | |
| 7 | 15 | |
| 8 | 9 | |
| 9 | 20 | |
| 10 | 114 | |
| 11 | MIXTURE OF GLMS AND THE TRIMMED LIKELIHOOD METHODOLOGY | 3 |
| 12 | 27 | |
| 13 | 17 | |
| 14 | 2 | |
| 15 | 11 |
About Plamen Neytchev
Plamen Neytchev is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Global and Planetary Change, having authored 15 papers that have together received 282 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (7 papers), Climate variability and models (5 papers) and Statistical Methods and Bayesian Inference (3 papers). The work is most often cited by research in Statistics and Probability (122 citations), Statistics, Probability and Uncertainty (36 citations) and Global and Planetary Change (89 citations). Plamen Neytchev has collaborated with scholars based in Bulgaria, Austria and Netherlands. Frequent co-authors include Neyko Neykov, Peter Filzmoser, Rositsa B. Dimova, Pieter van Gelder, Valentin Todorov, John de Ronde, Walter Zucchini, Pierre Bénard, Maja Telišman Prtenjak and Pavel Čı́žek. Their work appears in journals such as Water Resources Research, Monthly Weather Review and Remote Sensing.
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.