| Discipline name | Position | Best Scientists | Publications | D-Index |
|---|---|---|---|---|
| Mathematics | 244 | 30 | 41 | 11 |
| Engineering and Technology | 717 | 21 | 41 | 12 |
Technometrics is mainly concerned with subjects like Statistics, Econometrics, Applied mathematics, Mathematical optimization and Algorithm. Estimator, Regression analysis, Confidence interval, Regression and Sampling (statistics) are all areas of Statistics tackled in Technometrics.
The main points discussed in the published articles deal with Statistics, Econometrics, Applied mathematics, Mathematical optimization and Algorithm. The journal publications connects the study in Statistics with the closely related areas of Control chart. The studies tackled in the most cited publications, which mainly focus on Econometrics, apply to Regression as well.
The aim of Technometrics is to expand the discussion of research in Artificial intelligence, Algorithm, Bayesian probability, Series (mathematics) and Gaussian process. Technometrics facilitates discussions on Artificial intelligence that incorporate concepts from other fields like Machine learning and Pattern recognition. Pattern recognition research presented in it encompasses a variety of subjects, including Bayesian hierarchical modeling, Multivariate statistics and Regression.
The studies in Series (mathematics) featured incorporate elements of Data mining and Behavioural sciences. Function (mathematics), Sequential analysis, Design of experiments and Computer experiment are some topics wherein Gaussian process research discussed in the journal have an impact. The studies on Computer experiment discussed can also contribute to research in the domains of Uncertainty reduction theory and Mathematical optimization.
A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.
The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.
The top authors publishing in Technometrics (based on the number of publications) are:
The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.
Only papers with recognized affiliations are considered
The top affiliations publishing in Technometrics (based on the number of publications) are:
The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.
The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.
The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.
During the most recent 2021 edition, 21.43% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 34.85% were posted by at least one author from the top 10 institutions publishing in the journal. Another 12.12% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 12.12% of all publications and 40.91% were from other institutions.
A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.
The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.
The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.
Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).
The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:
The chart below illustrates experience levels of first authors in cases of publications with multiple authors.
Yichi Zhang;Siyu Tao;Wei Chen;Daniel W. Apley
(2020)Trevor Hastie
(2020)Mostafa Reisi Gahrooei;Hao Yan;Kamran Paynabar;Jianjun Shi
(2021)Peihua Qiu;Wendong Li;Jun Li
(2020)Wendong Li;Dongdong Xiang;Fugee Tsung;Xiaolong Pu
(2020)Jian-Feng Yang;Fasheng Sun;Hongquan Xu
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