Journal of Computational and Graphical Statistics
宗旨和范围
The Journal of Computational and Graphical Statistics is a quarterly peer-reviewed scientific journal published by Taylor & Francis on behalf of the American Statistical Association. Established in 1992, the journal covers the use of computational and graphical methods in statistics and data analysis, including numerical methods, graphical displays and methods, and perception. It is published jointly with the Institute of Mathematical Statistics and the Interface Foundation of North America. According to the Journal Citation Reports, the journal has a 2017 impact factor of 1.790. Less
关键指标
查看图表期刊详情
- 出版商TAYLOR & FRANCIS INC
- 出版语言English
- 出版频率Quarterly
- 出版语言English
- 出版频率Quarterly
- 创刊年份1992
- Publisher URL
- 网址
| 月数 | 发表论文百分比 |
|---|---|
| 0-3 | 0% |
| 4-6 | 1% |
| 7-9 | 9% |
| >9 | 90% |
Topics Covered
年度发行情况
- 5Y
- 10Y
常见问题
Journal of Computational and Graphical Statistics 是从何时开始发行的？ 
Journal of Computational and Graphical Statistics 自1992开始发行至今。
Journal of Computational and Graphical Statistics 多久发行一次？
Journal of Computational and Graphical Statistics 为Quarterly。
Journal of Computational and Graphical Statistics 的 H 指数、SNIP 指数、Citescore 和 SJR 分别是多少？
Journal of Computational and Graphical Statistics 的H指数为 97、 Citescore 为 3.8、SNIP 指数为1.79 、 SJR 为 Q1。
Journal of Computational and Graphical Statistics 的出版商是谁？
Journal of Computational and Graphical Statistics 的出版商是TAYLOR & FRANCIS INC。
我在哪里查看 Journal of Computational and Graphical Statistics 的宗旨和范围？
查看 Journal of Computational and Graphical Statistics 的宗旨和范围，请点击此处。
我如何在意得辑上查看Journal of Computational and Graphical Statistics 的指标？
查看 Journal of Computational and Graphical Statistics 的指标，请单击此处。
Journal of Computational and Graphical Statistics 的 eISSN和pISSN 号分别是什么？
1537-2715 的 eISSN 为 1061-8600，pISSN 为 Journal of Computational and Graphical Statistics 。
该期刊重点关注哪些主题？
本期刊关注的主题范围广泛，包括 Time series, Random forest, Sparse structure, Markov chain Monte Carlo, Principal component analysis, Gaussian process, Simulation, Deterministic approximation, Variance estimation, Time complexity, Tikhonov regularization, Discrete choice, Markov chain, Regression problems, Covariance matrix, Credible interval, Projection pursuit, Gaussian random field, Network analysis, Evolutionary algorithm。
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