Monthly Archives: October 2011

Netflix Post-mortem – How to detect Bubbles

October 26, 2011
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Netflix Post-mortem – How to detect Bubbles

Bubbles. I’m no expert in behavioral economics, but bubbles seem to be well understood (after they occur) although they seem hard to detect (at least in the eyes of outsiders and late bubble participants). This post won’t tell you how to avoid bubbles, but might give you some insight. I came across Minsky’s explanation of

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Mixed-Effects Models in R with Quantum Forest

October 26, 2011
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For anyone who wants to estimate linear or nonlinear mixed-effects models (aka random-effects models, hierarchical models or multilevel models) using the R language, the Quantum Forest blog has several recent posts that will be of interest. Written by Luis Apiolaza from the School of Forestry at the University of Canterbury in New Zealand, the blog includes a number of...

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What do your rules look like? editrules 1.8-x answers with the help of igraph

October 26, 2011
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What do your rules look like? editrules 1.8-x answers with the help of igraph

We (Edwin de Jonge and me) have recently updated our editrules package. The most important new features include (beta) support for categorical data. However, in this post I'm going to show some visualizations we included, made possible by Gabor Csardi's … Continue reading →

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How to display R code on a web page

October 26, 2011
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Starting to write a blog I need a way how to publish my R codes. One possibility would be to just add some formatting with Pretty R. Nice, but I miss a repository with all codes ever submitted and possibility to make corrections.The final solution was ...

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Covariance structures

October 26, 2011
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Covariance structures

In most mixed linear model packages (e.g. asreml, lme4, nlme, etc) one needs to specify only the model equation (the bit that looks like y ~ factors...) when fitting simple models. We explicitly say nothing about the covariances that complete … Continue reading →

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Two-sex demographic models in R

October 26, 2011
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Two-sex demographic models in R

Tom Miller (a prof here at Rice) and Brian Inouye have a paper out in Ecology (paper, appendices) that confronts two-sex models of dispersal with empirical data.They conducted the first confrontation of two-sex demographic models with empirical data on...

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Controlling multiple risk measures during construction of efficient frontier

October 26, 2011
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Controlling multiple risk measures during construction of efficient frontier

In the last few posts I introduced Maximum Loss, Mean-Absolute Deviation, and Expected shortfall (CVaR) and Conditional Drawdown at Risk (CDaR) risk measures. These risk measures can be formulated as linear constraints and thus can be combined with each other to control multiple risk measures during construction of efficient frontier. Let’s examine efficient frontiers computed

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PAWL package on CRAN

October 26, 2011
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PAWL package on CRAN

The PAWL package (which I talked about there, and which implements the parallel adaptive Wang-Landau algorithm and adaptive Metropolis-Hastings for comparison) is now on CRAN! http://cran.r-project.org/web/packages/PAWL/index.html which means that within R you can easily install it by typing install.packages("PAWL") Isn’t that amazing? It’s just amazing. Kudos to the CRAN team for their quickness and their

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New features in R-bloggers.com

October 26, 2011
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New features in R-bloggers.com

Hello dear R community, In the past few months I have rolled out a bunch of new features to R-bloggers, and I wanted to raise awareness to them.  Please consider giving some of these a try and leave me any feedback that you have (by leaving a comment on this post): Comments – it is now possible to leave comments in...

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Batch Processing vs. Interactive Sessions

October 26, 2011
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Batch Processing vs. Interactive Sessions

We introduced batch processing 3 weeks ago. Many people asked about differences and benefits of batch processing or interactive sessions. Lets start with the definitions: Batch Processing / Batch Jobs: Batch processing is the execution of a series of programs or only one task on a computer environment without manual intervention. All data and commands

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