Dynamic Linear Models with R (Use R) Giovanni Petris, Sonia Petrone, Patrizia Campagnoli
Publisher: Springer

The thing I found most impressive was its incredibly terse syntax for fitting a regression model. Getting the p-value and R2 onto the plot takes a little more doing. If there is something scipy is weak at that I need, I'll also use R in a pinch or move down to C. (Like Jockers, I (In a linear model, pronounGenderGap contributes absolutely nothing above PronounGap towards predicting AuthorshipGap: an absurdly high p=.96, where p<0 .05="" be="" significant.="" would=""> . I think you are basically operating at a disadvantage if you are using the other packages at this point. As he puts it succinctly "DSL: D, not L". These ads will give you all the to review score impressive savings. Make a system of linear equations using the two equilibria,. I can't walk you through the installation of Python and its modules (there's a huge amount of material already available, and if you use a Mac, I highly recommend the MacPorts installation route). This rather unlikely linguistic cocktail would What matters is how easy it is to get started and do common tasks like linear regression, handling data sets, etc. About what's good about R for its specific domain. The initial plot looks like this: The initial plot. A very reliable way to accomplish this merely Dynamic Linear Models With R (Use R!) Sale. Are words the atomic unit of a dynamic system? And adding the regression line from the linear model is as simple as: abline(r1). MATLAB (or Octave or Scilab) is great for roll-your-own statistical analyses as well, though I can't see using it for, e.g., a conventional linear models analysis unless I wanted the experience. The only other reason I can see to use .. R is a dynamic language for statistical computing that combines lazy functional features and object-oriented programming. The following chart (made with 8 lines of code in R and the forthcoming Bookworm API) shows the top 50 Library of Congress classifications in Bookworm, divided into male- and female-authored books. R can do any statistical tests and numerical modeling you can imagine; if there's not a built-in function you can write one (the beauty of using a programming language over point-and-click statistical programs).