- 學位論文
R語言區間象徵型資料矩陣視覺化探索式分析平台：iGAP套件
iGAP：Matrix visualization for interval value based on GAP framework in R
摘要
R 語言在統計領域非常熱門，許多新穎的統計研究方法都會發布成 R 語言的套件。本研究旨在 R 語言中實現廣義相關圖（Generalized Association Plots; GAP）以處理區間資料，能夠被 R 語言龐大的象徵型區間資料庫與演算法套件所支援。GAP 是矩陣視覺化（Matrix Visualization; MV）的擴展。特別著重於象徵型區間資料的探索性分析 (Exploratory data analysis; EDA)，在進行複雜統計方法之前能讓資料自述其故事。對此本研究開發出一款套件名為 iGAP，將 GAP 概念引入 R 中，使區間資料進行排列並視覺化，讓使用者能快速且清晰的了解到資料之間的關係與型樣。我們相信 GAP 作為一個進階的探索性資料分析工具，在 R 中不僅能應用在區間資料上，未來也能對各種資料型態進行推廣。
並列摘要
R language is highly popular in the statistical field, with many innovative statistical methods being released as R packages. This study aims to implement Generalized Association Plots (GAP) for interval data in R, supported by a vast repository of symbolic interval data and algorithmic packages in R. GAP is an extension of Matrix Visualization (MV). Focusing particularly on the Exploratory Data Analysis (EDA) of symbolic interval data, the study facilitates data to narrate its story before applying complex statistical methods. To this end, we have developed a package named iGAP, integrating the GAP concept into R, enabling the arrangement and visualization of interval data for users to quickly and clearly understand the relationships and patterns within the data. We believe that GAP, as an advanced tool for EDA in R, can be applied to interval data and potentially extended to various data types in the future.