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关 键 词：stata正版软件百度云盘
行 业：IT 软件 翻译软件
发布时间：2021-08-28
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。
Remarks and examples
Remarks are presented under the following headings:
What is Bayesian analysis?
Bayesian versus frequentist analysis, or why Bayesian analysis?
How to do Bayesian analysis
Advantages and disadvantages of Bayesian analysis
Brief background and literature review
Bayesian statistics
Posterior distribution
Selecting priors
Point and interval estimation
Comparing Bayesian models
Posterior prediction
Bayesian computation
Markov chain Monte Carlo methods
Metropolis–Hastings algorithm
Adaptive random-walk Metropolis–Hastings
Blocking of parameters
Metropolis–Hastings with Gibbs updates
Convergence diagnostics of MCMC
Summary
The first five sections provide a general introduction to Bayesian analysis. The remaining sections
provide a more technical discussion of the concepts of Bayesian analysis.
Building a reliable Bayesian model requires extensive experience from the researchers, which leads
to the second difficulty in Bayesian analysis—setting up a Bayesian model and performing analysis
is a demanding and involving task. This is true, however, to an extent for any statistical modeling
procedure.
Lastly, one of the main disadvantages of Bayesian analysis is the computational cost. As a rule,
Bayesian analysis involves intractable integrals that can only be computed using intensive numerical
methods. Most of these methods such as MCMC are stochastic by nature and do not comply with
the natural expectation from a user of obtaining deterministic results. Using simulation methods does
not compromise the discussed advantages of Bayesian approach, but unquestionably adds to the
complexity of its application in practice.
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.
Nonlinear DSGE models in Stata 15
In Stata 15, we introduced the dsge command for fitting linear DSGE models, which are time-series models used in economics and finance. These models are an alternative to traditional forecasting models. Both attempt to explain aggregate economic phenomena, but DSGE models do this on the basis of models derived from microeconomic theory.
New in Stata 16, the dsgenl command fits nonlinear DSGE models. Most DSGE models are nonlinear, and this means that you no longer need to linearize them by hand. When you enter equations into dsgenl, it linearizes them for you.
After estimating the parameters of your model with dsgenl, you can obtain the transition and policy matrices; determine the model’s steady state; estimate variables’ variances, covariances, and autocovariances implied by the system of equations; and create and graph impulse–response functions.
This is likely to be the favorite feature of macroeconomists and anyone working in a central bank.
19年来，公司始终秉承、专注、专心的发展理念，厚积薄发，积累了大量的人才、技术以及行业经验，在行业内得到了大量用户的认可和高度价。
