Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians (Hardcover)
暫譯: 貝葉斯思想與數據分析:科學家與統計學家的入門指南(精裝版)
Ronald Christensen, Wesley Johnson, Adam Branscum, Timothy E Hanson
- 出版商: CRC
- 出版日期: 2010-07-06
- 售價: $3,500
- 貴賓價: 9.5 折 $3,325
- 語言: 英文
- 頁數: 516
- 裝訂: Hardcover
- ISBN: 1439803544
- ISBN-13: 9781439803547
-
相關分類:
Data Science、機率統計學 Probability-and-statistics
立即出貨 (庫存=1)
買這商品的人也買了...
-
$660$627 -
$1,200$1,020 -
$3,770$3,582 -
$4,240$4,028 -
$780$663 -
$1,460$1,431 -
$3,500$3,325 -
$1,490Contemporary Artificial Intelligence (Hardcover)
-
$1,000$700 -
$980$833 -
$180$171 -
$580$493 -
$580$493 -
$680$578 -
$580$458 -
$380$342 -
$620$527 -
$560$437 -
$560$476 -
$220$187 -
$1,050$998 -
$1,872Deep Learning: A Practitioner's Approach (Paperback)
-
$3,580$3,401 -
$1,750Statistical Rethinking: A Bayesian Course with Examples in R and Stan (Hardcover)
-
$2,600$2,470
相關主題
商品描述
Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to collaborate in analyzing data. The WinBUGS code provided offers a convenient platform to model and analyze a wide range of data.
The first five chapters of the book contain core material that spans basic Bayesian ideas, calculations, and inference, including modeling one and two sample data from traditional sampling models. The text then covers Monte Carlo methods, such as Markov chain Monte Carlo (MCMC) simulation. After discussing linear structures in regression, it presents binomial regression, normal regression, analysis of variance, and Poisson regression, before extending these methods to handle correlated data. The authors also examine survival analysis and binary diagnostic testing. A complementary chapter on diagnostic testing for continuous outcomes is available on the book’s website. The last chapter on nonparametric inference explores density estimation and flexible regression modeling of mean functions.
The appropriate statistical analysis of data involves a collaborative effort between scientists and statisticians. Exemplifying this approach, Bayesian Ideas and Data Analysis focuses on the necessary tools and concepts for modeling and analyzing scientific data.
Data sets and codes are provided on a supplemental website.
商品描述(中文翻譯)
強調使用 WinBUGS 和 R 來分析實際數據的《Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians》提供了針對科學問題的統計工具。它突顯了統計學中的基礎問題、準確預測的重要性,以及科學家和統計學家在數據分析中合作的必要性。提供的 WinBUGS 代碼為建模和分析各種數據提供了一個方便的平台。
本書的前五章包含核心內容,涵蓋基本的貝葉斯思想、計算和推斷,包括來自傳統抽樣模型的一樣本和兩樣本數據建模。接著,文本介紹了蒙地卡羅方法,例如馬可夫鏈蒙地卡羅(MCMC)模擬。在討論回歸中的線性結構後,介紹了二項回歸、正態回歸、變異數分析和泊松回歸,然後將這些方法擴展到處理相關數據。作者還探討了生存分析和二元診斷測試。關於連續結果的診斷測試的補充章節可在本書網站上獲得。最後一章關於非參數推斷,探討了密度估計和均值函數的靈活回歸建模。
適當的數據統計分析需要科學家和統計學家之間的合作努力。《Bayesian Ideas and Data Analysis》以此方法為例,專注於建模和分析科學數據所需的工具和概念。
數據集和代碼可在補充網站上獲得。