Statistical Theory of Reliability and Life Testing-Probability Models
Impact in
- Journal
- Technometrics
In The Last Decade
doi.org/10.2307/1268641 →Countries where authors are citing Statistical Theory of Reliability and Life Testing-Probability Models
This map shows the geographic impact of Statistical Theory of Reliability and Life Testing-Probability Models. 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 Statistical Theory of Reliability and Life Testing-Probability Models with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Statistical Theory of Reliability and Life Testing-Probability Models more than expected).
Fields of papers citing Statistical Theory of Reliability and Life Testing-Probability Models
This network shows the impact of Statistical Theory of Reliability and Life Testing-Probability Models. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the Statistical Theory of Reliability and Life Testing-Probability Models.
About Statistical Theory of Reliability and Life Testing-Probability Models
This paper, published in 1977, received 3.0k indexed citations . Written by Donald R. Smith, Richard E. Barlow and Frank Proschan. It is primarily cited by scholars working on Statistics and Probability (1.6k citations), Safety, Risk, Reliability and Quality (1.1k citations), Statistics, Probability and Uncertainty (914 citations), Management Science and Operations Research (802 citations) and Software (394 citations). Published in Technometrics.
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.
This paper is also available at doi.org/10.2307/1268641.