Longitudinal Structural Equation Modeling, Todd D. Little, Guilford Press 2013.
Let me start by saying that this is one of the best textbooks I’ve ever read. It was written as if the author was our mentor, and I really get the feeling that he’s sharing his wisdom with us rather than trying to be pedagogically correct. The book is full of insights on how he thinks about building and applying SEMs, and the lessons he’s learned the hard way.
I’ve just discovered a unique app on the Mac App Store called Calca. It’s like a simple word-processor, except you can define variables and functions and do arithmetic with them, and it understands units and currencies and it handles matrices and vectors, and supports basic Markdown, and … it’s pretty amazing.
I just read about a website, accidental aRt, that shows how artistic R graphics can look when things go bad. Wonderful!
Percolation is the ability of a liquid-like substance to get through a solid-like lattice. An interesting question is how the likelihood of a material allowing percolation changes as the average density of the lattice changes from 100% (i.e. solid with no percolation) to 0% (i.e. nothing with total percolation). Read an interesting article that looks at the case of square lattices using R: Percolation Threshold on a Square Lattice
I just upgraded to MacOS X Mavericks and can highly recommend it. It’s an amazing update, especially considering it’s free. You may not be a Mac user, but one thing that is quite interesting is the degree that Apple has gone to save battery power in Mavericks.
Here’s a screen capture of the Activity Monitor’s Energy tab (click on it to see it full-sized):
I’ve been working with some linear programming (LP) lately, and have looked at a bunch of non-commercial, non-Academic-use tools for LP, and in particular IP (integer programming). Open source solvers I’ve looked at include:
Gnu GLPK’s glpsol