MORGAN

MORGAN is a software for genetic analysis using MCMC.

An example of MCMCglmm

Here is a very useful example of how to estimate multinomial logit with random effect using MCMCglmm package.

Kindle DX as a textbook reader

Here is an interesting argument for Kindle DX.

Useful blog

on using R, especially the MCMCglmm Package.

IRex

IRex seems to be a good alternative to Nook and Kindle. And it is running Linux! Also, its 8.1 inch screen will certainly make reading much more comfortable than the 6 inch Nook or Kindle.

IPad = IBad?

Interesting comments.

IPad

Apple's new toy, ipad, looks interesting. But 10 hour's battery life per charge seems to be less impressive than I originally thought. Some laptop computers can do that. Also, I was surprised to find out its operating system is IPhone OS instead of OSX.

Being an Apple product also means that, in order to do anything useful, you have to buy and buy and buy...

Submitting to a sociology journal

This blog has some useful information for those who are thinking about submitting to a sociology journal.

An online summary of different mortality estimates between 1959 and 1961

This online article provides a good summary.

Here is another one.

Here are some discussions.

VMware shortcut keys

Here is a list of useful shortcut keys for VMware.

Google may leave China

According to a CNN report, Google may pull their business out of China.

Word count for PDF (LaTeX) file

According to this site, This is as simple as one command line:

pdftotext yourfilename.pdf - | wc -w

Even more options can be found here.

Tutorial for XETEX

XETEX tutorial.

PyMC

PyMC is a Python implementation of MCMC sampling algorithm, looks very promising. Not it is in its second major release, with a full-blown manual. have the potential for a serious Bayesian package.

Event History Analysis with Stata

Book web site here.

Apophenia

The January 2010 source release of the Apophenia library cannot be compiled on my Ubuntu machines (64-bit 9.10 and 32-bit 9.04); but the developmental version (downloaded via git) compiles flawlessly. Not sure what is going on.

R AnalyticFlow

R AnalyticFlow is an interesting piece of software. From its web site:

"R AnalyticFlow is a software which enables
state-of-the-art data analysis by drawing analysis flowcharts.
You can effectively share processes of data analysis
in collaborative works"

A customized Ubuntu-based Chinese distro

Linux Deepin looks promising. But it does not seem to provide a 64-bit version.

Some Stata tips

Here are some useful Stata tips.

LyZ

LyZ, Zotero for LyX, looks promising.

ADMB 9.1

A new version of ADMB has just come out, on the first day of the new year!

Create LaTeX table for descriptive statistics using Estout

I want to create a table of descriptive statistics. To be more specific, The table should contains 6 rows and 4 columns, something like this:

Descriptive Statistics

-----------------------------------------------------------

Cohort A Cohort B Cohort C

-----------------------------------------------------------

Urban Residence 0.263 0.313 0.264

Years of Schooling 5.585 7.280 7.592

Ethnic Majority 0.928 0.918 0.915

Want Children 0.990 0.992 0.991

Ever Pregnant 0.991 0.987 0.992

-----------------------------------------------------------

Observations 3553 2450 4694

-----------------------------------------------------------

The official document for Estout provides some clues but does not make it crystal clear. Here are the steps I followed:

1. Generate an arbitrary variable;
2. Run regression, separately for each cohort;
3. Collect the results;
4. Make the table

Here are the code:

eststo clear

gen y=uniform()

quietly regress y urban eduy han want_birth preg if cohort==1, noconstant

estadd mean

eststo d1

quietly regress y urban eduy han want_birth preg if cohort==2, noconstant

estadd mean

eststo d2

quietly regress y urban eduy han want_birth preg if cohort==3, noconstant

estadd mean

eststo d3

esttab d1 d2 d3, cells(mean(fmt(%8.3f))) label nonotes nonumber nodepvars mtitles("Cohort A" "Cohort B" "Cohort C") width(1\hsize) title(Descriptive Statistics)