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METRON welcomes original articles on statistical methodology, statistical applications, or discussions of results achieved by statistical methods in different branches of science.
Sankhya, Series A, publishes original, high quality research articles in various areas of modern statistics, such as probability, theoretical statistics, mathematical statistics and machine learning. The areas are interpreted in a broad sense. Articles are judged on the basis of their novelty and technical correctness. Sankhya, Series B, primarily covers applied and interdisciplinary statistics including data sciences. Applied articles should preferably include analysis of original data of broad interest, novel applications of methodology and development of methods and techniques of immediate practical use. Authoritative reviews and comprehensive discussion articles in areas of vigorous current research are also welcome.
Japanese Journal of Statistics and Data Science is a leading international peer-reviewed journal publishing original research, clinical updates, and reviews indexed in Clarivate Web of Science (SCIE) with Q3 quartile ranking.
Journal of Statistical Theory and Practice is a leading international peer-reviewed journal publishing original research, clinical updates, and reviews indexed in Clarivate Web of Science (SCIE) with Q3 quartile ranking.
Sankhya, Series A, publishes original, high quality research articles in various areas of modern statistics, such as probability, theoretical statistics, mathematical statistics and machine learning. The areas are interpreted in a broad sense. Articles are judged on the basis of their novelty and technical correctness. Sankhya, Series B, primarily covers applied and interdisciplinary statistics including data sciences. Applied articles should preferably include analysis of original data of broad interest, novel applications of methodology and development of methods and techniques of immediate practical use. Authoritative reviews and comprehensive discussion articles in areas of vigorous current research are also welcome.
Statistical Inference for Stochastic Processes aims to publish high quality papers devoted to inference in either discrete or continuous time stochastic processes. This includes topics such as ARMA processes, GARCH processes and other time series models, as well as diffusion type processes, point processes, random fields and Markov processes. Papers related to spatial models and empirical processes are also within the scope of the journal. Special focus is placed on methodological advances and sound theoretical results, but submissions that expose potential applications of the developed theory to finance, insurance, economics, biology, physics and engineering are very much encouraged. Officially cited as: Stat Inference Stoch Process