Here’s another quote from Anthony O’Hagan’s book Bayesian Inference.
All classical inference statements … are probability statements about x given θ, phrased so as to appear to be probability statements about θ.
Emphasis in the original.
Month: May 2009
Programming book I wish someone would write: R, The Good Parts
Douglas Crockford’s book JavaScript: The Good Parts is terrific. Crockford is both a critic of and advocate for JavaScript. He’s quite frank about the language’s faults. His book is the clearest exposition of the pitfalls of JavaScript that I’ve seen. But he also believes there’s a great language at the heart of JavaScript. He doesn’t just complain about the bad parts; he explains how to avoid them. He has identified his recommended subset of the language. He has written programming style guide intended to increase the chances that JavaScript code does what the programmer intends. And he has written a tool, JSLint, to warn of potential problems. (Crockford reminds me of Luke Skywalker, convinced that there is good in Darth Vader and determined to rescue him from the dark side of the force.)
I wish someone would write a book for R analogous to the one Crockford wrote for JavaScript.
The R language has a lot in common with JavaScript. Both are Lisp-like languages at their core with C-like syntax. Both are dominant languages in their respective niches: R in academic statistics and JavaScript in web browsers. (R doesn’t have the monopoly in statistics that JavaScript has in the browser, but it’s still pervasive.) Both languages are powerful but maddening to debug. JavaScript has an undeserved reputation for being ugly because it is typically used to program the browser DOM; it’s the DOM that’s buggy and non-standard, not JavaScript. Similarly, R’s reputation may suffer from the numerous poorly written modules implemented in R.