Which D features to emphasize for academic review article

[Andrei Alexandrescu]

On 8/11/12 7:33 PM, Walter Bright wrote:
[snip]

Allow me to insert an opinion here. This post illustrates quite well how 
opinionated our community is (for better or worse).

The OP has asked a topical question in a matter that is interesting and 
also may influence the impact of the language to the larger community. 
Before long the thread has evolved into the familiar pattern of a debate 
over a minor issue on which reasonable people may disagree and that's 
unlikely to change. We should instead do our best to give a balanced 
high-level view of what D offers for econometrics.

To the OP - here are a few aspects that may deserve interest:

* Modeling power - from what I understand econometrics is 
modeling-heavy, which is more difficult to address in languages such as 
Fortran, C, C++, Java, Python, or the likes of Matlab.

* Efficiency - D generates native code for floating point operations and 
has control over data layout and allocation. Speed of generated code is 
dependent on the compiler, and the reference compiler (dmd) does a 
poorer job at it than the gnu-based compiler (gdc) compiler.

* Convenience - D is designed to "do what you mean" wherever possible 
and simplify common programming tasks, numeric or not. That makes the 
language comfortable to use even by a non-specialist, in particular in 
conjunction with appropriate libraries.

A few minuses I can think of:

- Maturity and availability of numeric and econometrics library is an 
obvious issue. There are some libraries (e.g. 
https://github.com/kyllingstad/scid/wiki) maintained and extended 
through volunteer effort.

- The language's superior modeling power and level of control comes at 
an increase in complexity compared to languages such as e.g. Python. So 
the statistician would need a larger upfront investment in order to reap 
the associated benefits.


Andrei