找回密码
 To register

QQ登录

只需一步,快速开始

扫一扫,访问微社区

Titlebook: Bayesian Methods for the Physical Sciences; Learning from Exampl Stefano Andreon,Brian Weaver Book 2015 Springer Nature Switzerland AG 2015

[复制链接]
楼主: 解放
发表于 2025-3-25 07:05:55 | 显示全部楼层
发表于 2025-3-25 08:36:04 | 显示全部楼层
发表于 2025-3-25 11:48:08 | 显示全部楼层
发表于 2025-3-25 17:12:42 | 显示全部楼层
发表于 2025-3-25 21:22:08 | 显示全部楼层
The Prior,ptions). We illustrate this concept with examples where the prior plays greatly different roles, from major to negligible. We also provide some advice on how to look for information useful for sculpting the prior.
发表于 2025-3-26 01:35:07 | 显示全部楼层
发表于 2025-3-26 07:54:44 | 显示全部楼层
Non-random Data Collection,vents or objects are over–represented in samples and difficult–to–collect are under–represented if not missing altogether. In this chapter we show how to account for non–random data collection to infer the properties of the population from the studied sample.
发表于 2025-3-26 10:15:15 | 显示全部楼层
Fitting Regression Models,ment errors of different amplitudes and an intrinsic variety in the studied populations, or an extra source of variability? A number of examples illustrate how to answer these questions and how to predict the value of an unavailable quantity by exploiting the existence of a trend with another, available, quantity.
发表于 2025-3-26 16:02:50 | 显示全部楼层
Book 2015 the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The ex
发表于 2025-3-26 18:17:32 | 显示全部楼层
 关于派博传思  派博传思旗下网站  友情链接
派博传思介绍 公司地理位置 论文服务流程 影响因子官网 SITEMAP 大讲堂 北京大学 Oxford Uni. Harvard Uni.
发展历史沿革 期刊点评 投稿经验总结 SCIENCEGARD IMPACTFACTOR 派博系数 清华大学 Yale Uni. Stanford Uni.
|Archiver|手机版|小黑屋| 派博传思国际 ( 京公网安备110108008328) GMT+8, 2025-7-8 15:46
Copyright © 2001-2015 派博传思   京公网安备110108008328 版权所有 All rights reserved
快速回复 返回顶部 返回列表