IML/SAS - useful in GI?

[entact]

I work in GI and everyone in my team uses SAS V9.2. I read about this other SAS application called IML/SAS (Interactive Matrix Language) which apparantly is more flexible and better at programming algorithms and for speed.

Does anyone have any experience using this in an actuarial capacity and if so, if it worth getting?

Thanks

 

[Oxymoron]

I work in GI and everyone in my team uses SAS V9.2. I read about this other SAS application called IML/SAS (Interactive Matrix Language) which apparantly is more flexible and better at programming algorithms and for speed.

Does anyone have any experience using this in an actuarial capacity and if so, if it worth getting?

Thanks

I use IML extensively and I highly recommend it for the reasons you've mentioned. I've also found that for complex non-linear optimizations, it runs way faster than the equivalent algorithm in MATLAB. Vectorization is also a lot more efficient in IML than in MALTAB.

The problem with IML, just like any other matrix based language, is that it stores the entire data in memory. This means there's severe restrictions on the amount/type of data that can be read. Debugging an IML error is also a challenge. IML isn't a useful tool for processing large data and producing reports etc - but if you want more flexibility and you can feed in summarized/small datasets (<2GB or so, assuming 8GB RAM installed in your PC), its the best way to program in SAS.

 

[Hobbs]

I use IML extensively and I highly recommend it for the reasons you've mentioned. I've also found that for complex non-linear optimizations, it runs way faster than the equivalent algorithm in MATLAB. Vectorization is also a lot more efficient in IML than in MALTAB.

The problem with IML, just like any other matrix based language, is that it stores the entire data in memory. This means there's severe restrictions on the amount/type of data that can be read. Debugging an IML error is also a challenge. IML isn't a useful tool for processing large data and producing reports etc - but if you want more flexibility and you can feed in summarized/small datasets (<2GB or so, assuming 8GB RAM installed in your PC), its the best way to program in SAS.

Given how cheap RAM is these days the "add ram until it fits" approach is quite workable.

Though, there are some employers who would rather pay for days of dev rather than buy a thousand dollars of memory.