Steffen Möritz
Impact in
- Environmental Engineering top 10%
- Air Quality Monitoring and Forecasting
- Hydrological Forecasting Using AI
- Global and Planetary Change top 10%
- Climate variability and models
- Plant Water Relations and Carbon Dynamics
Papers in
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- Data Stream Mining Techniques 1
- Data Analysis with R 1
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- Water Systems and Optimization 1
- Co-authors
- Thomas Bartz–Beielstein (1 shared paper)Gilberto Reynoso-Meza (1 shared paper)Víctor Henrique Alves Ribeiro (1 shared paper)Óscar Ribeiro (1 shared paper)Svenja Hummel (1 shared paper)Vincenza Frisardi (1 shared paper)Christian G. Huber (1 shared paper)Sílvia Ferrari (1 shared paper)
- Journals
- The R Journal (1 paper)Scientific Reports (1 paper)The Science of The Total Environment (1 paper)
- Partner nations
- GermanySwitzerlandItaly
In The Last Decade
Steffen Möritz
3 papers receiving 614 citations
Hit Papers
Peers
Comparison fields: 5 of 148
- Environmental Engineering 88
- Global and Planetary Change 126
- Signal Processing 52
- Water Science and Technology 52
- Statistics and Probability 29
Countries citing papers authored by Steffen Möritz
This map shows the geographic impact of Steffen Möritz'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 Steffen Möritz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steffen Möritz more than expected).
Fields of papers citing papers by Steffen Möritz
This network shows the impact of papers produced by Steffen Möritz. 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 Steffen Möritz. The network helps show where Steffen Möritz may publish in the future.
Co-authors
The 15 scholars most cited alongside Steffen Möritz, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | imputeTS: Time Series Missing Value Imputation in R Hit paper breakdown → | 2017 | 611 |
| 2 | 2020 | 14 | |
| 3 | 2024 | 3 | |
| 4 | A General Multivariate Imputation Framework [R package imputeR version 2.2] | 2020 | 0 |
About Steffen Möritz
Steffen Möritz is a scholar working on Artificial Intelligence, Civil and Structural Engineering, General Health Professions, Clinical Psychology and Oncology, having authored 4 papers that have together received 628 indexed citations. Recurring topics across this work include Water Systems and Optimization (1 paper), COVID-19 and healthcare impacts (1 paper), Data Stream Mining Techniques (1 paper), Statistical Methods and Inference (1 paper), Data Analysis with R (1 paper), Statistical Methods and Bayesian Inference (1 paper), Healthcare professionals’ stress and burnout (1 paper) and COVID-19 and Mental Health (1 paper). The work is most often cited by research in Environmental Engineering (88 citations), Global and Planetary Change (126 citations), Signal Processing (52 citations), Water Science and Technology (52 citations) and Statistics and Probability (29 citations). Steffen Möritz has collaborated with scholars based in Germany, Switzerland and Italy. Frequent co-authors include Thomas Bartz–Beielstein, Gilberto Reynoso-Meza, Víctor Henrique Alves Ribeiro, Óscar Ribeiro, Svenja Hummel, Vincenza Frisardi, Christian G. Huber, Sílvia Ferrari, Gwendolyn Mayer and Charles Benoy. Their work appears in journals such as The R Journal, Scientific Reports and The Science of The Total Environment.
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.