Journals in Statistics

Computational Statistics & Data Analysis

ISSN: 0167-9473

The Official Journal of the Network Computational and Methodological Statistics (CMStatistics) and the International Association of Statistical Computing (IASC)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: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), 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/environmenta... 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. 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 (social sciences, marketing, psychometrics, chemometrics, signal processing, medical statistics, environmentrics, statistical physics).IV) Statistical Data Science - The manuscripts concern with well-founded theoretical and applied data-driven research, with a significant computational or statistical methodological component for data analytics. Emphasis is given to comprehensive and reproducible research, including data-driven methodology, algorithms and software. This journal section serves as a complementary component to the network Computational and Methodological Statistics (CMStatistics).

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Econometrics and Statistics

ISSN: 2452-3062

Econometrics and Statistics is the official journal of the networks Computational and Financial Econometrics and Computational and Methodological Statistics. It publishes research papers in all aspects of econometrics and statistics and comprises of the two sections Part A: Econometrics and Part B: Statistics.Part A: Econometrics. Emphasis is given to methodological and theoretical papers containing substantial econometrics derivations or showing a potential of a significant impact in the broad area of econometrics. Topics of interest include the estimation of econometric models and associated inference, model selection, panel data, measurement error, Bayesian methods, and time series analyses. Simulations are considered when they involve an original methodology. Innovative papers in financial econometrics and its applications are considered. The covered topics include portfolio allocation, option pricing, quantitative risk management, systemic risk and market microstructure. Interest is focused as well on well-founded applied econometric studies that demonstrate the practicality of new procedures and models. Such studies should involve the rigorous application of statistical techniques, including estimation, inference and forecasting. Topics include volatility and risk, credit risk, pricing models, portfolio management, and emerging markets. Innovative contributions in empirical finance and financial data analysis that use advanced statistical methods are encouraged. The results of the submissions should be replicable. Applications consisting only of routine calculations are not of interest to the journal.Part B: Statistics. Papers providing important original contributions to methodological statistics inspired in applications are considered for this section. Papers dealing, directly or indirectly, with computational and technical elements are particularly encouraged. These cover developments concerning issues of high-dimensionality, re-sampling, dependence, robustness, filtering, and, in general, the interaction of mathematical methods, numerical implementations and the extra burden of analysing large and/or complex datasets with such methods in different areas such as medicine, epidemiology, biology, psychology, climatology and communication. Innovative algorithmic developments are also of interest, as are the computer programs and the computational environments that implement them as a complement.The journal consists, preponderantly, of original research. Occasionally, review and short papers from experts are published, which may be accompanied by discussions. Special issues and sections within important areas of research are occasionally published. The journal publishes as a supplement The Annals of Computational and Financial Econometrics.

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Journal of Econometrics

ISSN: 0304-4076

The Journal of Econometrics serves as an outlet for important, high quality, new research in both theoretical and applied econometrics. The scope of the Journal includes papers dealing with identification, estimation, testing, decision, and prediction issues encountered in economic research. Classical Bayesian statistics, experimental design, and machine learning methods are decidedly within the range of the Journal's interests.There are two types of submissions 1. Regular (open submissions):full length papers, orshort papers less than 15 pages.A Themed issue is a collection of regular (open)submissions on the same topic proposed and/or approved by the Co-Editors. A full list of Themed Issues currently open for submission can be found here. Proposals for themed issues can be sent to journalofeconometric... Invited papers The Co-Editors may invite contributions to“how to” papers on topics of interest in applied economics.“Annals Issues” to mark special events.

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Journal of Statistical Planning and Inference

ISSN: 0378-3758

The Journal of Statistical Planning and Inference offers itself as a multifaceted and all-inclusive bridge between classical aspects of statistics and probability, and the emerging interdisciplinary aspects that have a potential of revolutionizing the subject. While we maintain our traditional strength in statistical inference, design, classical probability, and large sample methods, we also have a far more inclusive and broadened scope to keep up with the new problems that confront us as statisticians, mathematicians, and scientists, such as clustering, post model selection inference, deep learning and random networks.We publish high quality articles in all branches of statistics, probability, discrete mathematics, machine learning, and bioinformatics. We also especially welcome well written and up to date review articles on fundamental themes of statistics, probability, machine learning, and general biostatistics. Thoughtful letters to the editors, interesting problems in need of a solution, and short notes carrying an element of elegance or beauty are equally welcome.We want to serve as the broadest international platform for high quality research on every aspect of our field, traditional and cutting edge. The quality and the breadth of our editorial board reflects that singular priority.

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Next Research

ISSN: 3050-4759

Next Research is a peer-reviewed multidisciplinary journal, publishing research spanning all scientific technical and medical communities.The journal is part of the Next family, a new suite of multidisciplinary journals from Elsevier spanning all branches of science. Managed by our dedicated team of in-house Editors, Next Research offers authors speed, consistency, innovation, flexibility, and ease of submission.Next Research is an inclusive venue for scientifically accurate manuscripts that meet the ethical and scientific publishing standards. It publishes all research topics across the fields of health sciences, physical sciences, life sciences and social sciences. Next Research publishes experimental, computational, and theoretical work, in traditional formats such as Original Research Articles, Communications and Reviews, as well as novel formats and video content.The journal provides authors with rigorous peer review ensuring articles adhere to a high technical standard, with rapid decisions and a highly visible platform for scientists to share their research.We believe that all rigorous research should be shared.

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Physica A: Statistical Mechanics and its Applications

ISSN: 0378-4371

Recognized by the European Physical SocietyPhysica A: Statistical Mechanics and its Applications publishes research in the field of statistical mechanics and its applications. Statistical mechanics sets out to explain the behaviour of macroscopic systems, or the large scale, by studying the statistical properties of the microscopic or nanoscopic constituents. Applications of the concepts and techniques of statistical mechanics include: applications to physical and physiochemical systems such as solids, liquids and gases, interfaces, glasses, colloids, complex fluids, polymers, complex networks, applications to economic and social systems (e.g. socio-economic networks, financial time series, agent based models, systemic risk, market dynamics, computational social science, science of science, evolutionary game theory, cultural and political complexity), and traffic and transportation (e.g. vehicular traffic, pedestrian and evacuation dynamics, network traffic, swarms and other forms of collective transport in biology, models of intracellular transport, self-driven particles), as well as biological systems (biological signalling and noise, biological fluctuations, cellular systems and biophysics); and other interdisciplinary applications such as artificial intelligence (e.g. deep learning, genetic algorithms or links between theory of information and thermodynamics/stati... physics.).Physica A does not publish research on mathematics (e.g. statistics) or mathematical methods (e.g. solving differential equations) unless an original application to a statistical physics problem is included. Also research on fluid mechanics intended for an engineering readership as well as ordinary economic/econometric... studies falls outside the scope of Physica A .Specific subfields covered by the journal are statistical mechanics applications to:Soft matterBiological systems and systems biologyChemical systemsEconophysics and sociophysicsTraffic and transportationPhase transitionsComplex systemsDeep learning, genetic algorithms and other methods of AIBenefits to authors We also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our Support Center

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Spatial Statistics

ISSN: 2211-6753

Spatial Statistics publishes articles on the theory and application of spatial and spatio-temporal statistics. It favours manuscripts that present theory generated by new applications, or in which new theory is applied to an important practical case. A purely theoretical study will only rarely be accepted. Pure case studies and algorithms without methodological development are not acceptable for publication.Spatial Statistics concerns the quantitative analysis of spatial and spatio-temporal data, including their statistical dependencies, heterogeneity, accuracy and uncertainties. Methodology for spatial statistics is typically found in probability theory, stochastic modelling and mathematical statistics as well as in information and computer science. Spatial statistics is used in mapping, assessing spatial data quality, sampling design optimisation, modelling of spatial structures, and drawing of valid inference and causality from a limited set of spatio-temporal data. Application fields include:• The physical domains, e.g. environment, climate, agriculture, ecology, geosciences oceanography and remote sensing. • The social/economic domains, e.g. epidemiology, population characteristics, and disease mapping.Spatial Statistics encourages the submission of short communications and case studies in spatial statistics (i.e. manuscripts up to 3000 words presenting novel spatial statistical applications).Spatia... Statistics aims to publish reproducible science. Authors are encouraged to submit and publish data, procedures, models and methods that support your research publication. It provides facilities to interlink those with your published articles.Spatial Statistics has an open attitude towards the latest developments in data science, deep learning and geoAI, as long as a substantial statistical component is present.

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Statistics & Probability Letters

ISSN: 0167-7152

Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature.Statistic... & Probability Letters is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission.The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of Statistics & Probability Letters is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability.The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published. We also plan to publish applications and case studies that demonstrate a novel use of existing techniques or have interesting innovative ideas about data collection, modelling or inference.

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Stochastic Processes and their Applications

ISSN: 0304-4149

An official journal of the Bernoulli Society for Mathematical Statistics and Probability.Stochast... Processes and their Applications is a mathematics journal that publishes papers on the theory and applications of stochastic processes.It is concerned with the following: concepts and techniquesmathematic... challenging questions in sciences and engineering.characte... properties,limit theoremsinferencecon... of stochastic processes.The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. Submissions are anonymously peer-reviewed.This journal has an Open Archive. All published items, including research articles, have unrestricted access and will remain permanently free to read and download 48 months after publication. All papers in the Archive are subject to Elsevier's user license.If you require any further information or help, please visit our Support Center.

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Health

Journals in Statistics

Computational Statistics & Data Analysis

Econometrics and Statistics

Journal of Econometrics

Journal of Statistical Planning and Inference

Next Research

Physica A: Statistical Mechanics and its Applications

Spatial Statistics

Statistics & Probability Letters

Stochastic Processes and their Applications