Scandinavian Actuarial Journal is a journal for actuarial sciences that deals, in theory and application, with mathematical methods for insurance and related matters. The bounds of actuarial mathematics are determined by the area of application rather than by uniformity of methods and techniques. Therefore, a paper of interest to Scandinavian Actuarial Journal may have its theoretical basis in probability theory, statistics, operations research, numerical analysis, computer science, demography, mathematical economics, or any other area of applied mathematics; the main criterion is that the paper should be of specific relevance to actuarial applications. It is the hope of the editors that the journal can promote progress in the development of actuarial methodology and the proliferation of established methods in practical actuarial work. A special workshop section is intended to stimulate cooperative efforts between practitioners and theoreticians to solve real-life actuarial problems. The workshop will be open for papers at any level of theoretical preparation, from mere descriptions of practical problems with pleas for help, via discussions and tentative solutions, to complete theoretical treatment of these problems. The journal also publishes survey articles and has a section for empirical studies. All articles are refereed. Scandinavian Actuarial Journal has been published since 1918. It is published for the Danish Society of Actuaries, the Actuarial Society of Finland, the Norwegian Society of Actuaries and the Swedish Society of Actuaries.
The Scandinavian Journal of Statistics is internationally recognised as one of the leading statistical journals in the world. It was founded in 1974 by four Scandinavian statistical societies. Today more than eighty per cent of the manuscripts are submitted from outside Scandinavia. It is an international journal devoted to reporting significant and innovative original contributions to statistical methodology, both theory and applications. The journal specializes in statistical modelling showing particular appreciation of the underlying substantive research problems. The emergence of specialized methods for analysing longitudinal and spatial data is just one example of an area of important methodological development in which the Scandinavian Journal of Statistics has a particular niche.
The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches.Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed.Publication office: Taylor & Francis, Inc., 325 Chestnut Street, Suite 800, Philadelphia, PA 19106.
The journal of SET-VALUED AND VARIATIONAL ANALYSIS: THEORY AND APPLICATIONS is devoted to variational aspects of mathematical analysis and its applications and to all the aspects involving set-valued mappings and related topics. The journals aims to serve both specialists and users of set-valued and variational analysis, promoting, in this way, strong interactions between them, with particular emphasis on applications. The scope of the journal includes variational principles and their applications to mathematical sciences, operations research, economics, applied sciences, and engineering; set-valued and generalized differential calculus; methods of set-valued and variational analysis in constrained optimization, calculus of variations, and optimal control of ordinary differential, functional differential, and partial differential equations; variational inequalities and their generalizations; variational convergence; fixed points of set-valued mappings; selections and parameterizations; differential, integral
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 without methodological development are not acceptable for publication.Spatial statistics concerns the quantitative analysis of spatial and spatio-temporal data, including their statistical dependencies, accuracy and uncertainties. Methodology for spatial statistics is typically found in probability theory, stochastic modelling and mathematical statistics as well as in information science. Spatial statistics is used in mapping, assessing spatial data quality, sampling design optimisation, modelling of dependence structures, and drawing of valid inference from a limited set of spatio-temporal data. Application fields includeThe physical domains, e.g. agriculture, geology, soil science, hydrology, ecology, mining, oceanography, forestry, air quality, remote sensingThe social/economic domains, e.g. spatial econometrics, epidemiology and disease mapping.Spatial Statistics aims to publish reproducible science. Authors are encouraged to submit and publish procedures and data, along with the manuscript.
Stat is an innovative electronic journal for the rapid publication of novel and topical research results, publishing compact articles of the highest quality in all areas of statistical endeavour. Its purpose is to provide a means of rapid sharing of important new theoretical, methodological and applied research. Stat is a joint venture between the International Statistical Institute and Wiley-Blackwell.
Stat is characterised by:
• Speed - a single-pass, high-quality review process that aims to publish within 30 days of submission. There is no revision cycle.
• Concision - a maximum article length of 10 pages of text, not including references.
• Supporting materials - inclusion of electronic supporting materials including graphs, video, software, data and images.
• Scope – addresses all areas of statistics and interdisciplinary areas
Stat is a scientific journal for the international community of statisticians and researchers and practitioners in allied quantitative disciplines.
Statistica Neerlandica publishes research and expository material about new developments in probability, statistics and operations research, and their applications in medical, agricultural, econometric, physical or social sciences and industry, commerce and government. The emphasis is on clarity, accessibility for the general reader, and applicability. In particular, Statistica Neerlandica shows how, for certain practical problems, statistics or operations research can play a valuable role in decision making.
Statistical Inference for Stochastic Processes is devoted to the following topics:Parametric, semiparametric and nonparametric inference in discrete and continuous time stochastic processes (especially: ARMA type processes, diffusion type processes, point processes, random fields, Markov processes).Analysis of time series. Spatial Models. Empirical Processes.Applications to finances, insurances, economics, biology, physics and engineering.Officially cited as: Stat Inference Stoch Process
Statistical Methods and Applications (SMA) is the official Journal of the Italian Statistical Society. This international journal fosters the development of statistical methodology and its applications in biological, demographic, economic, health, physical, social, and other scientific domains. In particular, the journal emphasizes investigations of methodological foundations and methods that have broad applications. SMA includes two sections. The first is devoted to statistical methodology, publishing original contributions in all fields of statistics. In addition, this section periodically publishes critical reviews and discussions on recent developments in statistical theory and methods. The second section publishes papers devoted to original and innovative applications of recent statistical methodology and complex approaches of statistical data analysis.Officially cited as: Stat Methods Appl
Statistical Methods in Medical Research is a highly ranked, peer reviewed scholarly journal and is the leading vehicle for review articles in all the main areas of medical statistics and therefore an essential reference for all medical statisticians. It is particularly useful for medical researchers dealing with data and provides a key resource for medical and statistical libraries, as well as pharmaceutical companies.This unique journal is devoted solely to statistics and medicine and aims to keep professionals abreast of the many powerful statistical techniques now available to the medical profession. As techniques are constantly adopted by statisticians working both inside and outside the medical environment, this review journal aims to satisfy the increasing demand for accurate and up-to-the-minute information.Why choose Statistical Methods in Medical Research?Covers all areas of medical statisticsFull of statistics and statistical techniquesContains the latest, accurate informationAn indispensable reference for medical statisticians, statistical libraries and pharmaceutical companies.
The primary aim of the journal is to publish original and high-quality articles that recognize statistical modelling as the general framework for the application of statistical ideas. Submissions must reflect important developments, extensions, and applications in statistical modelling. The journal also encourages submissions that describe scientifically interesting, complex or novel statistical modelling aspects from a wide diversity of disciplines, and submissions that embrace the diversity of applied statistical modelling.An important objective and exciting feature of the journal is that the reader should be able to reproduce the results presented in published articles, apply the published techniques to their own problems, and even develop their own extensions of the methodology. To achieve this authors are strongly encouraged to make data and software available over the internet through a website linked to the journal. The website address is http://stat.uibk.ac.at/SMIJThe journal aims to be the major resource for statistical modelling, covering both methodology and practice. Its goal is to be multidisciplinary in nature, promoting the cross-fertilization of ideas between substantive research areas, as well as providing a common forum for the comparison, unification and nurturing of modelling issues across different subjects.The journal will have three main themes:* New Methodology for papers on new statistical modelling ideas. These papers will be based upon a problem of real substantive interest with appropriate data.* Practical Applications for papers on interesting practical problems which are addressed using an existing or a novel adaptation of an existing modelling technique.* Tutorials & Reviews with papers on recent and cutting edge topics in statistical modelling.Since "Practical Applications" manuscripts are less common in statistics journals than the other two types, it is worth being more specific concerning the types of manuscripts that fall into this category. Manuscripts should describe statistical analyses of a subject area, where the proposed analyses have rarely (if ever) been done in the application field. This is not, however, sufficient for acceptance for publication. Manuscripts should also provide a thorough literature review of how data of this type are currently handled in the literature of the application area, a review of any applications of modern statistical methodology applied to data of its type in the area, and justification as to why the work is important to the subject area, and provides gains beyond current methodology applied to the field. The methodology used should be modern and reasonably sophisticated (although not necessarily innovative) and should have few or no applications so far in the subject area literature.The intention in publishing such manuscripts is to provide an opportunity for readers (including those from the application area) to see the potential to revolutionize data analysis in the field. It is also hoped that such publication would provide an outlet for statisticians who may get little recognition in the statistics field for excellent, non-routine, clever, state-of-the-art work in subject areas.It is expected that the author will submit several suggestions for possible reviewers who are in the application area when submitting the manuscript.
Statistical Papers provides a forum for the presentation and critical assessment of statistical methods. In particular, the journal encourages the discussion of methodological foundations as well as potential applications. This journal stresses statistical methods that have broad applications; however, it does give special attention to statistical methods that are relevant to the economic and social sciences. In addition to original research papers, readers will find survey articles, short notes, reports on statistical software, problem section, and book reviews.Officially cited as: Stat Papers