Rainer Göb

31 papers receiving 616 citations

Peers

Rainer Göb
Comparison fields: 5 of 123
  • Statistics, Probability and Uncertainty 147
  • Management Information Systems 146
  • Management Science and Operations Research 143
  • Statistics and Probability 87
  • Medical Laboratory Technology 16
Replace Tsung‐Shin Hsu with:
Tsung‐Shin Hsu Taiwan
Thomas M. Margavio United States
XinYing Chew Malaysia
John F. Kros United States
Sigifredo Laengle Chile
Alireza Pooya Iran
Joan M. Donohue United States
Min-Chun Yu Taiwan
Xueqing Wang China
B. Madhu Rao United States
Rainer Göb relative to Tsung‐Shin Hsu Taiwan Tsung‐Shin Hsu's profile →
Citations per field
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Citations per year

Countries citing papers authored by Rainer Göb

Since Specialization
Citations

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

Fields of papers citing papers by Rainer Göb

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Rainer Göb, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Rainer Göb Line = papers co-authored together Rainer Göb links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 33 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016150
2 2007139
3 2016108
4 201447
5 201332
6 200825
7 201118
8 201914
9 201112
10 201310
11 200810
12 20209
13 19948
14 20148
15 19967
16 20016
17 20066
18 19675
19 19685
20 20064

About Rainer Göb

Rainer Göb is a scholar working on Statistics, Probability and Uncertainty, Management Science and Operations Research, Statistics and Probability, Control and Systems Engineering and Artificial Intelligence, having authored 33 papers that have together received 648 indexed citations. Recurring topics across this work include Advanced Statistical Process Monitoring (13 papers), Forecasting Techniques and Applications (8 papers), Fault Detection and Control Systems (4 papers), Industrial Vision Systems and Defect Detection (3 papers), Scientific Measurement and Uncertainty Evaluation (3 papers), Energy Load and Power Forecasting (3 papers), Insurance and Financial Risk Management (2 papers) and Advanced Statistical Methods and Models (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (147 citations), Management Information Systems (146 citations), Management Science and Operations Research (143 citations), Statistics and Probability (87 citations) and Medical Laboratory Technology (16 citations). Rainer Göb has collaborated with scholars based in Germany, Italy and United States. Frequent co-authors include Antonio Pievatolo, M. F. Ramalhoto, Sajid Ali, Giuseppe Manco, Marco S. Reis, Xavier Tort‐Martorell, Shirley Coleman, Christian Weiß, Robert Blackburn and Inga‐Lena Darkow. Their work appears in journals such as Quality and Reliability Engineering International, Quality Engineering, Applied Stochastic Models in Business and Industry, International Journal of Reliability Quality and Safety Engineering and Quality & Quantity.

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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