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北京天演融智软件有限公司(科学软件网)前身是北京世纪天演科技有限公司,成立于2001年,专注为国内高校、科研院所和以研发为主的企事业单位提供科研软件和服务的国家。
The principles of Bayesian analysis date back to the work of Thomas Bayes, who was a Presbyterian
minister in Tunbridge Wells and Pierre Laplace, a French mathematician, astronomer, and physicist in
the 18th century. Bayesian analysis started as a simple intuitive rule, named after Bayes, for updating
beliefs on account of some evidence. For the next 200 years, however, Bayes’s rule was an
obscure idea. Along with the rapid development of the standard or frequentist statistics in 20th century,
Bayesian methodology was also developing, although with less attention and at a slower pace. One
of the obstacles for the progress of Bayesian ideas has been the lasting opinion among mainstream
statisticians of it being subjective. Another more-tangible problem for adopting Bayesian models in
practice has been the lack of adequate computational resources. Nowadays, Bayesian statistics is
widely accepted by researchers and practitioners as a valuable and feasible alternative.
Bayesian analysis proliferates in diverse areas including industry and government, but its application
in sciences and engineering is particularly visible. Bayesian statistical inference is used in econometrics
(Poirier [1995]; Chernozhukov and Hong [2003]; Kim, Shephard, and Chib [1998], Zellner [1997]);
education (Johnson 1997); epidemiology (Greenland 1998); engineering (Godsill and Rayner 1998);
genetics (Iversen, Parmigiani, and Berry 1999); social sciences (Pollard 1986); hydrology (Parent
et al. 1998); quality management (Rios Insua 1990); atmospheric sciences (Berliner et al. 1999); and
law (DeGroot, Fienberg, and Kadane 1986), to name a few.

Stata是一款完整的、集成的统计软件包,提供您需要的一切数据分析、数据管理和图形。
快速,简单并易于使用
点击式的界面和强大,直观的命令语言让Stata使用起来快速,并易于使用。
所有的分析结果都可以被复制和存档,并用来出版和审查。不管您什么时候写的内容,版本控制系统确保统计程序可继续生成同样的结果。
统计功能介绍
Stata使得大量的统计工具用于指尖
标准方法,如
基本表格和总结
案例对照分析
ARIMA
ANOVA 和MANOVA
线性回归
时间序列平滑
广义线性模型(GLM)
聚类分析
对比和比较
功率分析
样本选择
……
方法,如
当Stata执行您的分析或理解使用的方法时,Stata不会让您孤立无援或订购很多书籍来了解每个细节。
我们每一个数据管理功能都有完整的解释,并记录在案,并在实践中显示实际的例子。每一个估计都有完全记录,包含几个真实数据的例子,真正讨论如何解释结果。这些例子都给了数据,您可以直接在Stata中使用,甚至扩展您的分析。我们给您快速启动每一个功能,展示一些常用用途。想要了解更多细节,我们的方法和公式部分提供了计算的细节,我们参考部分会给出更多信息。
Stata是一个很大的软件包,包含了非常多的文档,**过27卷14,000页的内容。不用担心,在Help菜单中输入要搜索的内容,Stata会搜索到关键词、指数,甚至用户编写的程序包,这些会让您得到想要了解的一切。Stata包含了所有这些您想要的内容。

Panel-data ERMs
Extended regression models (ERMs) were a big new feature last release. The ERM commands fit models that account for three common problems that arise in observational data—endogenous covariates, sample selection, and treatment—either alone or in combination.
In Stata 16, we introduce the xteregress, xteintreg, xteprobit, and xteoprobit commands for fitting panel-data ERMs. This means ERMs can now account for the three problems we mentioned above and for within-panel correlation. These new commands fit random-effects linear, interval, probit, and ordered probit regression models. They allow random effects in one or all equations, and they allow random effects to be correlated across equations.
Researchers from all disciplines who work with observational (nonexperimental) data are interested in ERMs and will be excited about the new panel-data versions of these commands. However, different disciplines talk about these models differently.
Above, we referred to the problems ERMs solve as endogenous covariates, sample selection, treatment, and within-panel correlation. While this terminology is common in some disciplines such as economics, other disciplines may use other terms.
• Instead of panel-data and within-panel correlation, researchers may ask for models for multilevel (two-level) data that account for within-group correlation.
• Instead of endogenous covariates, researchers may ask for methods of dealing with unobserved confounding or unmeasured confounding.
• Instead of sample selection, researchers may be concerned about trials with informative dropout, nonignorable nonresponse, or outcomes missing not at random (MNAR).
• Instead of treatment, researchers may ask about methods for causal inference or estimating average treatment effects (ATEs).
The important message is that all disciplines are interested in ERMs, but they often speak different languages.

New reporting features in Stata 16:
• The dyndoc and markdown commands now create Word documents in addition to the HTML documents they previously created. Now, you can easily incorporate full Stata output and graphs with Markdown-formatted text to create customized Word documents.
• The Do-file Editor now provides syntax highlighting for Markdown language elements.
• The putdocx command now lets you include headers, footers, and page numbers. It also makes it easier to write large blocks of text.
• The html2docx command converts HTML documents, including CSS, to Word documents.
• The docx2pdf command converts Word documents to PDFs.
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