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I think the original comment about unboxed numbers was not referring to vector vs. scalar but to boxing of primitive types (integers/floats) in object or other

I think the original comment about unboxed numbers was not referring to vector vs. scalar but to boxing of primitive types (integers/floats) in object or other type wrappers: http://en.wikipedia.org/wiki/Object_type_(object-oriented_programming) http://en.wikipedia.org/wiki/Object_type_(object-oriented_pr.... It's easy to imagine situations where languages that directly support vector types could have performance benefits, especially on HW that supports vector instruction sets. On the other hand, languages that don't directly manipulate numbers in the native format of the CPU(s) will peform poorly for large datasets.

epistasis 13y ago
I still don't know what the OP's point is, then. There are vector types and there are list/object types in R. The advantage of vectors over scalars for this field. Having to have a special case in the language of vector length equal to one is a disadvantage when all modern workstation architectures are vector based for computation. R is basically Lisp with syntactic sugar for BLAS/ATLAS and incredibly easy bindings for FORTRAN, C, and C++. If this description doesn't sound like an amazing combination for an application domain, then it's not in R's sweet spot.
- freshhawk 13y ago
  Vectors vs scalars is a different issue than boxed/primitive types. Of course you want to be working with vectors for these kinds of problems. But the ability to work with vectors of primitives rather than vectors of boxed types is about enormous gains in efficiency and memory usage. This is one of the reasons that R is so slow compared to other tools.