天津財經(jīng)大學統(tǒng)計系吳敬(存儲版)
【正文】 itical Science: Introduction to the Virtual Issue. pdf Gary King ? Gary King is the Albert J. Weatherhead III University Professor at Harvard University one of 24 with the title of University Professor, Harvard‘s most distinguished faculty position. He is based in the Department of Government (in the Faculty of Arts and Sciences) and serves as Director of the Institute for Quantitative Social Science. King develops and applies empirical methods in many areas of social science research, focusing on innovations that span the range from statistical theory to practical application（ software） ? King has been elected Fellow in 6 honorary societies Andrew Gelman ? ? He has received the Outstanding Statistical Application award from the American Statistical Association, the award for best article published in the American Political Science Review, and the Council of Presidents of Statistical Societies award for outstanding contributions by a person under the age of 40. His books include Bayesian Data Analysis (with John Carlin, Hal Stern, and Don Rubin), Teaching Statistics: A Bag of Tricks (with Deb Nolan), Data Analysis Using Regression and Multilevel/Hierarchical Models (with Jennifer Hill), Red State, Blue State, Rich State, Poor State: Why Americans Vote the Way They Do (with David Park, Boris Shor, Joe Bafumi, and Jeronimo Cortina), and A Quantitative Tour of the Social Sciences (coedited with Jeronimo Cortina). ? Andrew has done research on a wide range of topics, including: vote, elections , democracy, police , social work structure, toxicology。 ? 貝葉斯統(tǒng)計學在二十一世紀初更受歡迎 。結合后驗和先驗信息，貝葉斯 法則 產生了模型 1 比模型 2 有利的后驗機會比率 ： ????21222211112121)()()()()()()()()()(????????dpXfdpXfXpMpXpMpXMpXMp 后驗比率 = 先驗比率 / 數(shù)據(jù) * 貝葉斯因子 計算 ? 通過 MCMC方法隨機模擬得到邊緣后驗分布 ? MCMC方法是使用馬爾科夫鏈的蒙特卡羅積分，其基本思想是：構造一條 Markov 鏈使其平穩(wěn)分布為待估參數(shù)的后驗分布，通過這條馬爾科夫鏈產生后驗分布的樣本，并基于馬爾科夫鏈達到平穩(wěn)分布時的樣本 (有效樣本 )進行蒙特卡羅積分。 ? Martin A D, Saunders K L. Bayesian Inference for Political Science Panel Data[C]（政治學 Panel數(shù)據(jù)貝葉斯推斷） //American Political Science Association. 2020. ? Darmofal D. Bayesian spatial survival models for political event processes[J]（政治事件進程貝葉斯空間生存模型） . American J
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