Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization

Wiley, Matt, Wiley, Joshua F.

Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
  • 出版商: Apress
  • 出版日期: 2019-02-21
  • 售價: $2,800
  • 貴賓價: 9.5 折 $2,660
  • 語言: 英文
  • 頁數: 638
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1484228715
  • ISBN-13: 9781484228715
  • 相關分類: R 語言、Machine Learning

    • 立即出貨 (庫存=1)

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商品描述

Carry out a variety of advanced statistical analyses including generalized additive models, mixed effects models, multiple imputation, machine learning, and missing data techniques using R. Each chapter starts with conceptual background information about the techniques, includes multiple examples using R to achieve results, and concludes with a case study.
Written by Matt and Joshua F. Wiley, Advanced R Statistical Programming and Data Models shows you how to conduct data analysis using the popular R language. You'll delve into the preconditions or hypothesis for various statistical tests and techniques and work through concrete examples using R for a variety of these next-level analytics. This is a must-have guide and reference on using and programming with the R language.
What You'll Learn

  • Conduct advanced analyses in R including: generalized linear models, generalized additive models, mixed effects models, machine learning, and parallel processing
  • Carry out regression modeling using R data visualization, linear and advanced regression, additive models, survival / time to event analysis
  • Handle machine learning using R including parallel processing, dimension reduction, and feature selection and classification
  • Address missing data using multiple imputation in R
  • Work on factor analysis, generalized linear mixed models, and modeling intraindividual variability

Who This Book Is For
Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to perform more advanced analytics. Particularly, researchers and data analysts in the social sciences may benefit from these techniques. Additionally, analysts who need parallel processing to speed up analytics are given proven code to reduce time to result(s).

商品描述(中文翻譯)

執行各種進階統計分析，包括廣義加法模型、混合效應模型、多重插補、機器學習和缺失數據技術，使用R語言。每一章節都以關於技術的概念背景資訊開始，並使用R進行多個實例來達到結果，最後以一個案例研究作結。

由Matt和Joshua F. Wiley所著，《進階R統計程式設計和數據模型》向您展示如何使用流行的R語言進行數據分析。您將深入研究各種統計測試和技術的前提條件或假設，並通過使用R進行各種進階分析的具體示例來進行實踐。這是一本必備的使用和編程R語言的指南和參考書。

您將學到什麼：

- 在R中進行進階分析，包括：廣義線性模型、廣義加法模型、混合效應模型、機器學習和並行處理
- 使用R進行回歸建模，包括數據可視化、線性和進階回歸、加法模型、生存/時間事件分析
- 使用R進行機器學習，包括並行處理、維度降低、特徵選擇和分類
- 在R中處理缺失數據，使用多重插補
- 處理因子分析、廣義線性混合模型和建模個體內變異性

這本書適合對R和基本統計技術（如線性回歸）有一定了解的工作專業人士、研究人員或學生，他們想要學習如何使用R進行更高級的分析。特別是社會科學領域的研究人員和數據分析師可能會從這些技術中受益。此外，需要並行處理以加快分析速度的分析師將獲得減少結果時間的驗證代碼。

作者簡介

Matt Wiley is a tenured, associate professor of mathematics with awards in both mathematics education and honour student engagement. He earned degrees in pure mathematics, computer science, and business administration through the University of California and Texas A&M systems. He serves as director for Victoria College's quality enhancement plan and managing partner at Elkhart Group Limited, a statistical consultancy. With programming experience in R, C++, Ruby, Fortran, and JavaScript, he has always found ways to meld his passion for writing with his joy of logical problem solving and data science. From the boardroom to the classroom, Matt enjoys finding dynamic ways to partner with interdisciplinary and diverse teams to make complex ideas and projects understandable and solvable.
Joshua F. Wiley is a lecturer in the Monash Institute for Cognitive and Clinical Neurosciences and School of Psychological Sciences at Monash University and a senior partner at Elkhart Group Limited, a statistical consultancy. He earned his PhD from the University of California, Los Angeles, and his research focuses on using advanced quantitative methods to understand the complex interplays of psychological, social, and physiological processes in relation to psychological and physical health. In statistics and data science, Joshua focuses on biostatistics and is interested in reproducible research and graphical displays of data and statistical models. Through consulting at Elkhart Group Limited and former work at the UCLA Statistical Consulting Group, he has supported a wide array of clients ranging from graduate students, to experienced researchers, and biotechnology companies. He also develops or co-develops a number of R packages including varian, a package to conduct Bayesian scale-location structural equation models, and MplusAutomation, a popular package that links R to the commercial Mplus software.

作者簡介(中文翻譯)

Matt Wiley是一位經驗豐富的數學副教授，擁有數學教育和優秀學生參與方面的獎項。他通過加州大學和德克薩斯A&M系統獲得了純數學、計算機科學和工商管理學位。他擔任維多利亞學院品質提升計劃的主任，並在統計諮詢公司Elkhart Group Limited擔任管理合夥人。他在R、C++、Ruby、Fortran和JavaScript等編程語言方面有豐富的經驗，一直將寫作的熱情與邏輯問題解決和數據科學的樂趣相結合。從會議室到教室，Matt喜歡找到與跨學科和多樣化團隊合作的動態方式，使複雜的想法和項目變得易於理解和解決。

Joshua F. Wiley是蒙納士大學認知和臨床神經科學研究所和心理學科學學院的講師，也是統計諮詢公司Elkhart Group Limited的高級合夥人。他在加州大學洛杉磯分校獲得博士學位，他的研究重點是使用先進的定量方法來理解心理、社會和生理過程在心理和身體健康方面的複雜相互作用。在統計和數據科學方面，Joshua專注於生物統計，並對可重複研究和數據和統計模型的圖形顯示感興趣。通過在Elkhart Group Limited的諮詢工作和在UCLA統計諮詢小組的前任工作，他支持了各種客戶，從研究生到經驗豐富的研究人員和生物技術公司。他還開發或共同開發了一些R包，包括varian，一個用於進行貝葉斯比例-位置結構方程模型的包，以及MplusAutomation，一個將R與商業Mplus軟件鏈接的熱門包。

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