Chapter 4 R for Statistical Analysis

• Some features of R language

  • Dynamic typing (== type inference?)
  • Lexical scoping
  • Object oriented (everything is an object)
  • Functional programming?
    • Pattern 1: pass a function as an argument to another function, e.g. apply, lapply

• Limitations of R

  • Inability to scale (due to single threaded computing paradigm and poor memory management)

  • R is a memory bound language

    It spends almost all of its time reading and writing vector intermediates to memory”.^{R_is_memory_bound}

• Other potential topics

  • OOP in R^oop_in_r: S3, S4, Reference Classes and R.oo package

^{R_is_memory_bound}. Quoted from Advanced R Performance. ↩

^oop_in_r. This stackoverflow page has a short overview on what oop systems are available in R. A more detailed discussion can be found on Hadley's wiki page. ↩