R Environments, Scoping, and Evaluation With Some Applications

IF 0.5 4区数学 Q3 STATISTICS & PROBABILITY

Australian & New Zealand Journal of Statistics Pub Date : 2026-03-30 DOI:10.1111/anzs.70044

Ross Ihaka

引用次数: 0

Abstract

This paper aims to expose one of R's important features that seems to be little-known by most users. The particular feature is language scoping, which R inherits from languages like Algol60 and Scheme. Although the feature is comparatively little known, it is quite important, and knowing about it can change the way that R is used. Rather than proceeding as a technical exposition, the content is presented as a series of examples. These are formatted (without continuation prompts) so that they are easy to copy and paste. The right way to read the paper is to copy the examples and experiment with them.

查看原文本刊更多论文

一些应用程序的R环境，范围和评估

本文旨在揭示R的一个重要特性，而大多数用户似乎都不知道这个特性。特别的特性是语言作用域，这是R从Algol60和Scheme等语言继承的。虽然这个特性相对来说鲜为人知，但它非常重要，了解它可以改变R的使用方式。本文的内容不是作为技术说明进行的，而是作为一系列示例呈现的。这些都是格式化的（没有继续提示），以便于复制和粘贴。阅读论文的正确方法是抄写例子并进行实验。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Australian & New Zealand Journal of Statistics 数学-统计学与概率论

CiteScore

1.30

自引率

9.10%

发文量

审稿时长

>12 weeks

期刊介绍： 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.