商品描述
Introduction to Bayesian Econometrics: A GUIded Toolkit Using R offers a practical, conceptually clear, and computationally accessible pathway into Bayesian data analysis. Designed for readers who wish to apply Bayesian methods without necessarily investing years in programming, the book combines rigorous treatment of foundational ideas with a graphical user interface (GUI) that allows users to run Bayesian regression models in a user-friendly environment.
The first part develops the mathematical foundations of Bayesian inference by presenting all derivations step-by-step. This transparent treatment of conjugate models, including posterior analysis, marginal likelihoods, and posterior predictive distributions, provides readers with a strong theoretical base for the more advanced material that follows.
The second part focuses on implementation. It introduces the custom GUI for readers with little or no programming experience, demonstrates how to fit Bayesian models using established R packages, and guides more advanced users through programming key components of Bayesian samplers from scratch. This integrated approach enables readers with different backgrounds to engage with Bayesian methods at their preferred level of computational depth.
The third part extends the framework to modern Bayesian econometrics. It covers Bayesian machine learning, causal inference, and approximate methods, illustrating how Bayesian ideas can be applied to contemporary empirical challenges. By combining theory, software, and hands-on computation, the book provides a comprehensive entry point into both classical and modern Bayesian analysis.
Across all parts, the book is designed to support a wide range of users -beginners, intermediate programmers, and advanced learners-. To the best of the author's knowledge, no existing text combines mathematical transparency, software accessibility, and modern Bayesian topics in a single, integrated resource.
商品描述(中文翻譯)
《貝葉斯計量經濟學導論：使用 R 的引導工具包》提供了一條實用、概念清晰且計算上可及的貝葉斯數據分析途徑。這本書旨在幫助希望應用貝葉斯方法的讀者，而不必花費多年時間在程式設計上，結合了對基礎概念的嚴謹處理與圖形用戶界面（GUI），使用戶能夠在友好的環境中運行貝葉斯回歸模型。
第一部分通過逐步呈現所有推導，發展貝葉斯推斷的數學基礎。這種對共軛模型的透明處理，包括後驗分析、邊際似然和後驗預測分佈，為讀者提供了強大的理論基礎，以便後續更高級的內容。
第二部分專注於實作。它為幾乎沒有程式設計經驗的讀者介紹了自訂的 GUI，演示如何使用已建立的 R 套件來擬合貝葉斯模型，並指導更高級的用戶從零開始編程貝葉斯取樣器的關鍵組件。這種綜合方法使不同背景的讀者能夠以他們所偏好的計算深度參與貝葉斯方法。
第三部分將框架擴展到現代貝葉斯計量經濟學。它涵蓋了貝葉斯機器學習、因果推斷和近似方法，說明了貝葉斯思想如何應用於當代實證挑戰。通過結合理論、軟體和實際計算，這本書提供了一個全面的入口，進入古典和現代的貝葉斯分析。
在所有部分中，這本書旨在支持廣泛的用戶——初學者、中級程式設計師和高級學習者。據作者所知，尚無現有文本能在單一綜合資源中結合數學透明性、軟體可及性和現代貝葉斯主題。
作者簡介
Andrés Ramírez-Hassan is a Distinguished Professor at Universidad EAFIT whose work advances Bayesian econometrics and applied statistical modeling. His research has appeared in journals such as the Journal of Applied Econometrics, Econometric Reviews, and the International Journal of Forecasting. He has served as a researcher and consultant for global institutions, including the United Nations Development Programme and the Inter-American Development Bank. He was a Research Fellow in the Department of Econometrics and Business Statistics at Monash University, and a Visiting Professor at the University of Melbourne.
作者簡介(中文翻譯)
安德烈斯·拉米雷斯-哈桑（Andrés Ramírez-Hassan）是EAFIT大學的特聘教授，他的研究推進了貝葉斯計量經濟學和應用統計建模。他的研究成果發表於《應用計量經濟學期刊》（Journal of Applied Econometrics）、《計量經濟學評論》（Econometric Reviews）和《國際預測期刊》（International Journal of Forecasting）等期刊。他曾擔任全球機構的研究員和顧問，包括聯合國開發計劃署和美洲開發銀行。他曾在莫納什大學的計量經濟學與商業統計系擔任研究員，並在墨爾本大學擔任訪問教授。
