Australian & New Zealand Journal Of Statistics

杂志介绍

Australian & New Zealand Journal Of Statistics杂志介绍

《Australian & New Zealand Journal Of Statistics》是一本以English为主的未开放获取国际优秀期刊，中文名称澳大利亚和新西兰统计杂志，本刊主要出版、报道数学-STATISTICS & PROBABILITY领域的研究动态以及在该领域取得的各方面的经验和科研成果，介绍该领域有关本专业的最新进展，探讨行业发展的思路和方法，以促进学术信息交流，提高行业发展。该刊已被国际权威数据库SCIE收录，为该领域相关学科的发展起到了良好的推动作用，也得到了本专业人员的广泛认可。该刊最新影响因子为0.8，最新CiteScore 指数为1.7。

本刊近期中国学者发表的论文主要有：

• Efficient Inference for Longitudinal Data Varying

  Author: sc2010310134

• Statistical Analysis of Heat Waves in the State of Victoria in Australia

  Author: wongtst

英文介绍

Australian & New Zealand Journal Of Statistics杂志英文介绍

The Australian & New Zealand Journal of Statistics is an international journal managed jointly by the Statistical Society of Australia and the New Zealand Statistical Association. Its purpose is to report significant and novel contributions in statistics, ranging across articles on statistical theory, methodology, applications and computing. The journal has a particular focus on statistical techniques that can be readily applied to real-world problems, and on application papers with an Australasian emphasis. Outstanding articles submitted to the journal may be selected as Discussion Papers, to be read at a meeting of either the Statistical Society of Australia or the New Zealand Statistical Association.

The main body of the journal is divided into three sections.

The Theory and Methods Section publishes papers containing original contributions to the theory and methodology of statistics, econometrics and probability, and seeks papers motivated by a real problem and which demonstrate the proposed theory or methodology in that situation. There is a strong preference for papers motivated by, and illustrated with, real data.

The Applications Section publishes papers demonstrating applications of statistical techniques to problems faced by users of statistics in the sciences, government and industry. A particular focus is the application of newly developed statistical methodology to real data and the demonstration of better use of established statistical methodology in an area of application. It seeks to aid teachers of statistics by placing statistical methods in context.

The Statistical Computing Section publishes papers containing new algorithms, code snippets, or software descriptions (for open source software only) which enhance the field through the application of computing. Preference is given to papers featuring publically available code and/or data, and to those motivated by statistical methods for practical problems.