Model-Based Clustering, Classification, and Density Estimation Using mclust in R
暫譯: 使用 R 中的 mclust 進行基於模型的聚類、分類與密度估計

Scrucca, Luca, Fraley, Chris, Murphy, T. Brendan

Model-Based Clustering, Classification, and Density Estimation Using mclust in R
  • 出版商: CRC
  • 出版日期: 2023-04-20
  • 售價: $2,740
  • 貴賓價: 9.5 折 $2,603
  • 語言: 英文
  • 頁數: 242
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1032234954
  • ISBN-13: 9781032234953

    • 海外代購書籍(需單獨結帳)

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商品描述

Model-based clustering and classification methods provide a systematic statistical approach to clustering, classification, and density estimation via mixture modeling. The model-based framework allows the problems of choosing or developing methods to be understood within the context of statistical modeling. The mclust package for the statistical environment R is a widely-adopted platform implementing these model-based strategies. The package includes both summary and visual functionality, complementing procedures for estimating and choosing models.

Key features of the book:

  • An introduction to the model-based approach and the mclust R package
  • A detailed description of mclust and the underlying modeling strategies
  • An extensive set of examples, color plots and figures along with the R code for reproducing them
  • Supported by a companion website, including the R code to reproduce the examples and figures presented in the book, errata, and other supplementary material

The book is accessible to quantitatively trained students and researchers with a basic understanding of statistical methods, including inference and computing. In addition to serving as a reference manual for mclust, the book will be particularly useful to those wishing to employ these model-based techniques in research or applications in statistics, data science, clinical research, social science, and many other disciplines.

商品描述(中文翻譯)

模型基礎的聚類和分類方法提供了一種系統的統計方法，通過混合建模進行聚類、分類和密度估計。模型基礎的框架使得選擇或開發方法的問題能夠在統計建模的背景下理解。統計環境 R 的 mclust 套件是一個廣泛採用的平台，實現了這些模型基礎的策略。該套件包括摘要和視覺功能，補充了估計和選擇模型的程序。

本書的主要特點：


  • 介紹模型基礎的方法和 mclust R 套件

  • 詳細描述 mclust 及其底層建模策略

  • 提供大量示例、彩色圖表和圖形，以及重現這些圖形的 R 代碼

  • 配有伴隨網站，包括重現書中示例和圖形的 R 代碼、勘誤表及其他補充材料

本書適合具備基本統計方法（包括推斷和計算）理解的定量訓練學生和研究人員。除了作為 mclust 的參考手冊外，本書對於希望在統計、數據科學、臨床研究、社會科學及其他許多學科中應用這些模型基礎技術的人特別有用。

作者簡介

Luca Scrucca
Associate Professor of Statistics at Università degli Studi di Perugia, his research interests include: mixture models, model-based clustering and classification, statistical learning, dimension reduction methods, genetic and evolutionary algorithms. He is currently Associate Editor for the Journal of Statistical Software and Statistics and Computing. He has developed and he is the maintainer of several high profile R packages available on The Comprehensive R Archive Network (CRAN).

Chris FraleyMost recently a lead research staff member at Tableau, she previously held research positions in Statistics at the University of Washington and at Insightful from its early days as Statistical Sciences. She has contributed to computational methods in a number of areas of applied statistics, and is the principal author of several widely-used R packages. She was the originator (at Statistical Sciences) of numerical functions such as nlminb that have long been available in the R core stats package.

T. Brendan MurphyProfessor of Statistics at University College Dublin, his research interests include: model-based clustering, classification, network modeling and latent variable modeling. He is interested in applications in social science, political science, medicine, food science and biology. He served as Associate Editor for the journal Statistics and Computing, he is currently Editor for the Annals of Applied Statistics and Associate Editor for Statistical Analysis and Data Mining.

Adrian Raftery
Boeing International Professor of Statistics and Sociology, and Adjunct Professor of Atmospheric Sciences at the University of Washington, Seattle. He is also a faculty affiliate of the Center for Statistics and the Social Sciences and the Center for Studies in Demography and Ecology at University of Washington. He was one of the founding researchers in model-based clustering, having published in the area since 1984. His research interests include: model-based clustering, Bayesian statistics, social network analysis and statistical demography. He is interested in applications in social, environmental, biological and health sciences. He is a member of the U.S. National Academy of Sciences and was identified by Thomson-Reuter as the most cited researcher in mathematics in the world for the decade 1995--2005. He served as Editor of the Journal of the American Statistical Association (JASA).

作者簡介(中文翻譯)

Luca Scrucca
佩魯賈大學統計學副教授，他的研究興趣包括：混合模型、基於模型的聚類與分類、統計學習、降維方法、遺傳演算法與進化演算法。他目前擔任《統計軟體與計算期刊》的副編輯，並且是多個高知名度的 R 套件的開發者及維護者，這些套件可在綜合 R 套件庫 (CRAN) 上獲得。

Chris Fraley最近擔任 Tableau 的首席研究人員，之前在華盛頓大學和 Insightful（早期名為 Statistical Sciences）擔任統計學研究職位。她在多個應用統計領域貢獻了計算方法，並且是幾個廣泛使用的 R 套件的主要作者。她是數值函數的創始人（在 Statistical Sciences），例如 nlminb，這些函數早已在 R 核心統計套件中提供。

T. Brendan Murphy都柏林大學統計學教授，他的研究興趣包括：基於模型的聚類、分類、網絡建模和潛變量建模。他對社會科學、政治科學、醫學、食品科學和生物學的應用感興趣。他曾擔任《統計與計算期刊》的副編輯，目前是《應用統計年鑑》的編輯和《統計分析與數據挖掘》的副編輯。

Adrian Raftery
華盛頓大學西雅圖校區的波音國際統計與社會學教授，以及大氣科學的兼任教授。他也是華盛頓大學統計與社會科學中心及人口學與生態學研究中心的教職員夥伴。他是基於模型的聚類的創始研究者之一，自1984年以來在該領域發表過多篇論文。他的研究興趣包括：基於模型的聚類、貝葉斯統計、社會網絡分析和統計人口學。他對社會、環境、生物和健康科學的應用感興趣。他是美國國家科學院的成員，並被湯森路透評選為1995年至2005年十年間全球數學領域被引用最多的研究者。他曾擔任《美國統計協會期刊》（JASA）的編輯。

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