政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/149650

政大機構典藏-National Chengchi University Institutional Repository(NCCUR):Item 140.119/149650

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题名:	dataSDA: 用於象徵型資料分析的資料集之 R 套件 dataSDA: Data Sets for Symbolic Data Analysis in R
作者:	陳柏維 Chen, Po-Wei
贡献者:	吳漢銘 Wu, Han-Ming 陳柏維 Chen, Po-Wei
关键词:	區間值資料直方圖值資料 R 套件象徵型資料分析 interval-valued data histogram-valued data R package symbolic data analysis
日期:	2023
上传时间:	2024-02-01 11:41:51 (UTC+8)
摘要:	在傳統資料集的範疇下，分析對象通常被局限於由單一觀察值構成的資料集合。然而，隨著資料的量與複雜性持續增加，資料收集已變得更為龐大和多樣化。為了更加有效地整合管理資料並保留其中蘊含的關鍵資訊，資料收集的變數格式已經超越了單一數值，轉而採用了包含區間、直方圖、機率分佈等在內的多值描述方式，這種資料描述形式被稱作「象徵型資料」。通過這種描述方式，我們能更全面地掌握資料的分佈、特性和變異性，有助於進一步的數據分析和解釋。本研究開發了一個名為 dataSDA 的 R 語言套件。這個套件的主要目標是針對不同的研究主題來收集各種象徵型資料，並進行不同格式的象徵型資料的讀取、寫出及轉換，以及計算象徵型資料的描述性統計量。此套件參考了當前廣泛使用的象徵型資料套件 RSDA 和 HistDAWass的格式架構，並在功能上進行了擴展，例如，從傳統資料依不同條件整合出一象徵型資料。我們利用 dataSDA 套件中的資料集進行了分群、分類和迴歸分析的演示和比較。我們相信，dataSDA 作為一個象徵型資料的收集和處理工具，能夠成為一個重要的象徵型資料來源，並能有效地協助使用者深入象徵型資料分析研究領域，進一步發展象徵型資料的分析方法。dataSDA 套件已發佈在 the Comprehensive R Archive Network (CRAN) 供人下載使用。 Within the context of traditional datasets, the subjects of analysis are typically restricted to data collections composed of singular values of variables. However, as the volume and complexity of data continue to grow, data collection has become increasingly vast and diverse. To more effectively consolidate and manage data while preserving the essential information it contains, the format of data variables has evolved beyond singular values. Instead, it now adopts multivalued descriptive methods that encompass intervals, histograms, and probability distributions. This representation of data is termed ”symbolic data.” Through this descriptive method, we can gain a more comprehensive grasp of the data’s distribution, characteristics, and variability, facilitating further data analysis and interpretation. This study introduced an R package named dataSDA. The primary aim of this package is to gather various symbolic data tailored to different research themes, and to execute the reading, writing, and conversion of symbolic data in diverse formats, as well as compute the descriptive statistics of symbolic variables. This package draws inspiration from the structural framework of widely-used symbolic data packages, RSDA and HistDAWass, and has expanded its functionalities such as generating symbolic data by aggregation of the conventional data. We utilized benchmark datasets within the dataSDA package to demonstrate and compare clustering, classification, and regression analyses in R. We believe that dataSDA, serving as a tool for the collection and processing of symbolic data, can stand as a pivotal source for symbolic data. It holds the potential to effectively guide users deeper into the realm of symbolic data analysis research, fostering the development of analytical methods for symbolic data. The dataSDA package is currently available on the Comprehensive R Archive Network (CRAN).
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描述:	碩士國立政治大學統計學系 111354013
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