Mathematical Sciences: Statistical Graphics: Foundations of Regression Graphics

实时、计算密集型、图形化方法， 回归是本研究的重点。 特别是 将强调理论统计基础和 标准显示的含义，如图族 基于一大类围参数模型的残差 包括广义线性模型。 这项研究的一个目标是 是开发一个纯粹的图形分析与模型评估 不源于残差的方法。 这些发展 将作为基于LISP的计算的扩展 环境XLISP-STAT。 定量数据的图形显示是一个核心工具 科学探索的一部分 虽然这些在历史上 仅限于任何可以在二维纸张上呈现的内容 纸，计算技术现在通常允许三个- 三维图形显示。 如何使有效和 技术上有效的科学使用这项技术需要谨慎 思考和合理的治疗。 反过来，这将导致 更好地理解标准显示器和 建设更有效的。

Real-time, computationally intensive, graphical methods for regression are the focus of this research. In particular, it will emphasize the theoretical statistical foundations and the implications of standard displays such as the family of plots based on residuals for a broad class of peri-parametric models including generalized linear models. One goal of this research is to develop a purely graphical analysis with model assessment methods that do not originate in residuals. These developments will be available as extensions of the LISP-based computing environment XLISP-STAT. Graphical displays of quantitative data are a central tool of scientific inquiry. Although these have historically been limited to whatever could be presented on a two-dimensional sheet of paper, computing technology now routinely allows three- dimensional graphical displays. How to make effective and technically valid scientific use of this technology needs careful thought and a logical treatment. In turn, this should result in both a better understanding of standard displays and the construction of still more effective ones.