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 The Official Journal of the International Association for Statistical Computing
Editor-in-Chief:
S.P. Azen
See editorial board for all editors information
Call for papers: 5th CSDA Special Issue on COMPUTATIONAL ECONOMETRICS
Deadline: 15 October 2008
Call for Papers: Special Issue on MODEL SELECTION and ROBUST PROCEDURES
Deadline: 30 November 2008
Call for Papers: 3rd CSDA Special Issue on MATRIX COMPUTATIONS AND STATISTICS
Deadline: 15 December 2008
Meet Stan Azen: an Editor's profile
CSDA Bibliography on Computational and Financial Econometrics
Description
Computational Statistics & Data Analysis (CSDA), the official journal of the International Association
of 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 three refereed sections, and a fourth section dedicated
to news on statistical computing. The refereed sections 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,
computational econometrics, 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, econometrics, environmetrics, education, image
analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures,
Statistical methodology includes, but not limited to: bootstrapping, classification techniques, clinical trials , data exploration,
density estimation, design of experiments, pattern recognition/image analysis, parametric and nonparametric methods, statistical genetics,
Bayesian modeling, outlier detection, robust procedures, cross-validation, functional data, fuzzy statistical analysis, mixture models,
model selection and assessment, nonlinear models, partial least squares, latent variable models, structural equation models, supervised
learning, signal extraction and filtering, time-series modelling, longitudinal analysis, multilevel analysis and quality control.
III) Special Applications - Manuscripts at the interface of statistics
and computing (e.g., comparison of statistical methodologies,
computer-assisted instruction for statistics, simulation experiments). Advanced statistical analysis with real applications (economics,
social sciences, marketing, psychometrics, chemometrics, signal processing, finance, medical statistics, environmentrics, statistical
physics).
| Bibliographic details |
ISSN: 0167-9473
Imprint: ELSEVIER
Commenced publication 1983
Subscriptions for the year 2009,
Volume 53,
12 issues |
For an overview of recently-dispatched issues, see the Journal issue
dispatch dates
Audience
Statisticians (university, government, business, industry), Statistical Software users.
Impact factor of this journal
2007: 1.029
© Journal Citation Reports 2008, published by Thomson Reuters
600/151
Last update: 10 Oct 2008
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