BayesPostEst

 Finally a modern Bayesian implementation of the Zelig package here.

NetLogoR

NetLogoR is the first serious ABS system implemented in pure R language, and it is based on the proven NetLogo framework.

Statistics doesn't have to be so hard: simulate!

I ought to show this video to my students.

Zelig 4 is trouble

Zelig 4 is causing so many problems. I had to uninstall it and went back to the old 3.55.

Jamsim

Jamsim is a microsimulation took utilizing R and Java. It looks fascinating. Its documentation can improve in the future.

Game of life

Implemented in various languages, including R.

Here is a Python version.

Another one.

Simulate parameters

This blog shows how to simulate parameters from a tobit model with a few line of R code.

Simulating second difference using Zelig

I am trying to simulate second difference using Zelig, here is my code:
--------------------------------------------------------

data(turnout)


# estimation


z.out <- zelig(vote ~ race*age + educate + income,
               model = "logit", data = turnout)


summary(z.out)


# first difference


x.low <- setx(z.out, educate = 12)
x.high <- setx(z.out, educate = 16)


s.out <- sim(z.out, x = x.low, x1 = x.high)


s.low <- sim(z.out, x=x.low)
s.high <- sim(z.out, x=x.high)


dif <- (s.high$qi$ev - s.low$qi$ev)


# second difference


x.low.low <- setx(z.out, educate = 12, age = 20)
x.low.high <- setx(z.out, educate = 12, age = 30)
x.high.low <- setx(z.out, educate = 16, age = 20)
x.high.high <- setx(z.out, educate = 16, age = 30)


s1 <- sim(z.out, x = x.low.low, x1 = x.low.high)
s2 <- sim(z.out, x = x.high.low, x1 = x.high.high)


did1 <- s1$qi$fd - s2$qi$fd


# or equivalent


s3 <- sim(z.out, x = x.low.low, x1 = x.high.low)
s4 <- sim(z.out, x = x.low.high, x1 = x.high.high)


did2 <- s3$qi$fd - s4$qi$fd

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

It would be great if Zelig can do this directly though. 

NetLogo-R-Extension

Here is a bridge between NetLogo and R, which looks very interesting. But I was not able to get it work on my Ubuntu box (running the latest R).

Programming in NetLogo

Here is a nice introduction to NetLogo from a programming language perspective.

Statistical simulation

Chapter 7 of Data Analysis Using Regression and Multilevel/Hierarchical Models by Gelman and Hill offers good description of why use statistical simulation in quantitative research. Their R package ARM provides a good place to get started to program one's own simulation module. Of course, Zelig has already had a impressive collection of models pre-programmed; but custom programming is always more fun.

Simcol

This R package (http://simecol.r-forge.r-project.org/) looks interesting. For one thing: it can do Conway's game of life.

Stata equavalence to Zelig

The R package Zelig can generate meaningful results such as predicted value, expected value, first difference, etc. from a wide variety of statistical procedures via simulation or bootstrapping. The Stata module "prvalue" and "prgen" seem to do at least a subset of what Zelig can do. Interestingly, the authors did not mention Gary King's work on Zelig and "Clarify".

However, it does not seem to work with mixed effect models.

Predict, simulate, and graph aML results

The multilevel and multiprocess software aML is quite amazing. It handles a much greater number of models than most other packages, and it is fast to reach convergence given suitable starting values. However, it does not have lots of facilities for results presentation.

I have used this software for several of my own research. I think it will be highly desirable to streamline the communication between aML and Stata or R. I can think of the following steps:

1. Estimate a mode in aML;
2. Extract point estimates and variance/covariance from the output file using Python;
3. Transfer the extracted results to R;
4. Predict, simulate, and graph the results with Zelig or other facilities built into R.
   

A good new book on Monte Carlo methods

Title: Simulation and Monte Carlo: With applications in finance and MCMC
Author: J. S. Dagpunar
Publisher: Wiley

This new book seems really cool and I will try to remember to buy it next time I visit US.

http://as.wiley.com/WileyCDA/WileyTitle/productCd-0470854952.html