Computational Statistics & Data Analysis SCIE

國(guó)際簡(jiǎn)稱：COMPUT STAT DATA AN 參考譯名：計(jì)算統(tǒng)計(jì)和數(shù)據(jù)分析

主要研究方向：數(shù)學(xué)-計(jì)算機(jī)：跨學(xué)科應(yīng)用非預(yù)警期刊審稿周期：較快,2-4周

《計(jì)算統(tǒng)計(jì)和數(shù)據(jù)分析》(Computational Statistics & Data Analysis)是一本由Elsevier出版的以數(shù)學(xué)-計(jì)算機(jī)：跨學(xué)科應(yīng)用為研究特色的國(guó)際期刊，發(fā)表該領(lǐng)域相關(guān)的原創(chuàng)研究文章、評(píng)論文章和綜述文章，及時(shí)報(bào)道該領(lǐng)域相關(guān)理論、實(shí)踐和應(yīng)用學(xué)科的最新發(fā)現(xiàn)，旨在促進(jìn)該學(xué)科領(lǐng)域科學(xué)信息的快速交流。該期刊是一本未開放期刊，近三年沒(méi)有被列入預(yù)警名單。

3區(qū) 中科院分區(qū)
Q2 JCR分區(qū)
134 年發(fā)文量
1.5 IF影響因子
未開放 是否OA
93 H-index
1983 創(chuàng)刊年份
Monthly 出版周期
English 出版語(yǔ)言

Computational Statistics and Data Analysis (CSDA), an Official Publication of the network Computational and Methodological Statistics (CMStatistics) and of the International Association for Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of four refereed sections which are divided into the following subject areas:

I) Computational Statistics - Manuscripts dealing with: 1) the explicit impact of computers on statistical methodology (e.g., Bayesian computing, bioinformatics,computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, heuristics, knowledge based systems, machine learning, neural networks, numerical and optimization methods, parallel computing, statistical databases, statistical systems), and 2) the development, evaluation and validation of statistical software and algorithms. Software and algorithms can be submitted with manuscripts and will be stored together with the online article.

II) Statistical Methodology for Data Analysis - Manuscripts dealing with novel and original data analytical strategies and methodologies applied in biostatistics (design and analytic methods for clinical trials, epidemiological studies, statistical genetics, or genetic/environmental interactions), chemometrics, classification, data exploration, density estimation, design of experiments, environmetrics, education, image analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures.

[...]

III) Special Applications - [...]

IV) Annals of Statistical Data Science [...]

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Computational Statistics & Data Analysis期刊信息

ISSN：0167-9473
出版語(yǔ)言：English
是否OA：未開放
E-ISSN：1872-7352
出版地區(qū)：NETHERLANDS
是否預(yù)警：否
出版商：Elsevier
出版周期：Monthly
創(chuàng)刊時(shí)間：1983
開源占比：0.0862
Gold OA文章占比：25.33%
OA被引用占比：0.0678...
出版國(guó)人文章占比：0.2
出版撤稿占比：0
研究類文章占比：100.00%

Computational Statistics & Data Analysis CiteScore評(píng)價(jià)數(shù)據(jù)（2024年最新版）

CiteScore

SJR

SNIP

CiteScore 指數(shù)

3.7

1.008

1.42

學(xué)科類別	分區(qū)	排名	百分位
大類：Mathematics 小類：Statistics and Probability	Q1	56 / 278	80%
大類：Mathematics 小類：Applied Mathematics	Q2	166 / 635	73%
大類：Mathematics 小類：Computational Mathematics	Q2	63 / 189	66%
大類：Mathematics 小類：Computational Theory and Mathematics	Q2	64 / 176	63%

名詞解釋：CiteScore 是衡量期刊所發(fā)表文獻(xiàn)的平均受引用次數(shù)，是在 Scopus 中衡量期刊影響力的另一個(gè)指標(biāo)。當(dāng)年CiteScore 的計(jì)算依據(jù)是期刊最近4年（含計(jì)算年度）的被引次數(shù)除以該期刊近四年發(fā)表的文獻(xiàn)數(shù)。例如，2022年的 CiteScore 計(jì)算方法為：2022年的 CiteScore =2019-2022年收到的對(duì)2019-2022年發(fā)表的文件的引用數(shù)量÷2019-2022年發(fā)布的文獻(xiàn)數(shù)量注：文獻(xiàn)類型包括：文章、評(píng)論、會(huì)議論文、書籍章節(jié)和數(shù)據(jù)論文。

Computational Statistics & Data Analysis中科院評(píng)價(jià)數(shù)據(jù)

中科院 2023年12月升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	數(shù)學(xué)	3區(qū)	STATISTICS & PROBABILITY 統(tǒng)計(jì)學(xué)與概率論 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 計(jì)算機(jī)：跨學(xué)科應(yīng)用	3區(qū) 4區(qū)

中科院 2022年12月升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	數(shù)學(xué)	3區(qū)	COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 計(jì)算機(jī)：跨學(xué)科應(yīng)用 STATISTICS & PROBABILITY 統(tǒng)計(jì)學(xué)與概率論	3區(qū) 3區(qū)

中科院 2021年12月舊的升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	數(shù)學(xué)	3區(qū)	COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 計(jì)算機(jī)：跨學(xué)科應(yīng)用 STATISTICS & PROBABILITY 統(tǒng)計(jì)學(xué)與概率論	3區(qū) 3區(qū)

中科院 2021年12月基礎(chǔ)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	數(shù)學(xué)	3區(qū)	COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 計(jì)算機(jī)：跨學(xué)科應(yīng)用 STATISTICS & PROBABILITY 統(tǒng)計(jì)學(xué)與概率論	4區(qū) 3區(qū)

中科院 2021年12月升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	數(shù)學(xué)	3區(qū)	COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 計(jì)算機(jī)：跨學(xué)科應(yīng)用 STATISTICS & PROBABILITY 統(tǒng)計(jì)學(xué)與概率論	3區(qū) 3區(qū)

中科院 2020年12月舊的升級(jí)版

Top期刊	綜述期刊	大類學(xué)科		小類學(xué)科
否	否	數(shù)學(xué)	3區(qū)	COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS 計(jì)算機(jī)：跨學(xué)科應(yīng)用 STATISTICS & PROBABILITY 統(tǒng)計(jì)學(xué)與概率論	3區(qū) 3區(qū)

Computational Statistics & Data Analysis JCR評(píng)價(jià)數(shù)據(jù)（2023-2024年最新版）

按JIF指標(biāo)學(xué)科分區(qū)	收錄子集	分區(qū)	排名	百分位
學(xué)科：COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS	SCIE	Q3	126 / 169	25.7%
學(xué)科：STATISTICS & PROBABILITY	SCIE	Q2	43 / 168	74.7%

按JCI指標(biāo)學(xué)科分區(qū)	收錄子集	分區(qū)	排名	百分位
學(xué)科：COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS	SCIE	Q3	86 / 169	49.41%
學(xué)科：STATISTICS & PROBABILITY	SCIE	Q2	60 / 168	64.58%

Computational Statistics & Data Analysis歷年數(shù)據(jù)統(tǒng)計(jì)

影響因子

中科院分區(qū)

Computational Statistics & Data Analysis中國(guó)學(xué)者發(fā)文選摘

1、Sparse spatially clustered coefficient model via adaptive regularization
Author: Zhong, Yan; Sang, Huiyan; Cook, Scott J.; Kellstedt, Paul M.

Journal: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2023; Vol. 177, Issue , pp. -. DOI: 10.1016/j.csda.2022.107581
2、Estimation for partial functional partially linear additive model
Author: Tang, Qingguo; Tu, Wei; Kong, Linglong

Journal: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2023; Vol. 177, Issue , pp. -. DOI: 10.1016/j.csda.2022.107584
3、Specification testing for ordinary differential equation models with fixed design and applications to COVID-19 epidemic models
Author: Liu, Ran; Zhu, Lixing

Journal: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2023; Vol. 180, Issue , pp. -. DOI: 10.1016/j.csda.2022.107616
4、Empirical Gittins index strategies with ?-explorations for multi-armed bandit problems
Author: Li, Xiao; Li, Yuqiang; Wu, Xianyi

Journal: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2023; Vol. 180, Issue , pp. -. DOI: 10.1016/j.csda.2022.107610
5、Generalized martingale difference divergence: Detecting conditional mean independence with applications in variable screening
Author: Li, Lu; Ke, Chenlu; Yin, Xiangrong; Yu, Zhou

Journal: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2023; Vol. 180, Issue , pp. -. DOI: 10.1016/j.csda.2022.107618
6、Applications on linear spectral statistics of high-dimensional sample covariance matrix with divergent spectrum
Author: Zhang, Yangchun; Zhou, Yirui; Liu, Xiaowei

Journal: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2023; Vol. 178, Issue , pp. -. DOI: 10.1016/j.csda.2022.107617
7、Optimal designs for semi-parametric dose-response models under random contamination
Author: Yu, Jun; Meng, Xiran; Wang, Yaping

Journal: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2023; Vol. 178, Issue , pp. -. DOI: 10.1016/j.csda.2022.107615
8、Multivariate sparse Laplacian shrinkage for joint estimation of two graphical structures
Author: Yang, Yuehan; Xia, Siwei; Yang, Hu

Journal: COMPUTATIONAL STATISTICS & DATA ANALYSIS. 2023; Vol. 178, Issue , pp. -. DOI: 10.1016/j.csda.2022.107620