Monday, May 20, 2013
Another option for R/LaTeX/Sweave editor
WinEdt is another good option for R/LaTeX/Sweave editing. I especially the feature of running "knitr + pdflatex" without opening a R terminal. Unfortunately it is a Windows-only software.
Saturday, May 11, 2013
Thursday, May 09, 2013
Glmer2stan
Glmer2stan is an interesting software that translates glmer (lme4) syntax into Stan. The software is still at eary stage but looks very promising.
Wednesday, May 08, 2013
Sumatra pdf viewer
The Sumatry pdf viewer works very well on Windows platform. If you have to run LaTeX on Windows platform and needs function like auto-update of the compiled pdf file, Sumatry is the right choice.
Friday, May 03, 2013
Rstudio vs. StatET
Rstudio wins in easy installation, smaller size, and intuitive user interface. StatET wins in graphical debugger and an outline view. Right now, StatET is a better choice for Sweave/Knitr/LaTeX authoring platform than Rstudio.
Sunday, April 14, 2013
Stan as a unified statistical estimation and intepretation engine
Applied researchers who are used to Stata or R need a reason to learn and use Stan. Besides the usual Bayesian vs. frequentist discussions, there is also a practical one.
Stan provides a unified interface for statistical estimation and interpretation. I have been using R with the Zelig package for estimation and interpretation during the past years, which is great. The problem is that, because Zelig is built upon a large number of existing R packages written by many different researchers and the quality of these packages vary greatly, working with Zelig means that you are working with all these other packages and researchers as well. In addition, even though in theory you can modify the source of these packages to suite your needs, but applied researches rarely have the energy or skills to tweak the FORTRAN or C code.
Stan provides a modeling language, which makes it easy for user to tweak their model (of course the underlying C++ code is also available). It is simulation-based and uses posterior distribution for inference, which means that there is no need for an additional simulation step (as what Zelig brings to frequentist models). After some testing, I have come to the conclusion that Stan is fast and stable enough for my daily data analysis work.
The best of all, this package comes from a research group with very good reputation and their discussion list is unbelievably helpful.
These are good enough reasons for me to switch to Stan.
Stan provides a unified interface for statistical estimation and interpretation. I have been using R with the Zelig package for estimation and interpretation during the past years, which is great. The problem is that, because Zelig is built upon a large number of existing R packages written by many different researchers and the quality of these packages vary greatly, working with Zelig means that you are working with all these other packages and researchers as well. In addition, even though in theory you can modify the source of these packages to suite your needs, but applied researches rarely have the energy or skills to tweak the FORTRAN or C code.
Stan provides a modeling language, which makes it easy for user to tweak their model (of course the underlying C++ code is also available). It is simulation-based and uses posterior distribution for inference, which means that there is no need for an additional simulation step (as what Zelig brings to frequentist models). After some testing, I have come to the conclusion that Stan is fast and stable enough for my daily data analysis work.
The best of all, this package comes from a research group with very good reputation and their discussion list is unbelievably helpful.
These are good enough reasons for me to switch to Stan.
Tuesday, April 09, 2013
Monday, April 08, 2013
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