How to deal with underflow in scientific computing?

Question

I am working on probabilistic models, and when doing inference on those models, the estimated probabilities can become very small. In order to avoid underflow, I am currently wo

Answer 1

Option 1: Commons Math - The Apache Commons Mathematics Library

Commons Math is a library of lightweight, self-contained mathematics and statistics components addressing the most common problems not available in the Java programming language or Commons Lang.

Note: The API protects the constructors to force a factory pattern while naming the factory DfpField (rather than the somewhat more intuitive DfpFac or DfpFactory). So you have to use

new DfpField(numberOfDigits).newDfp(myNormalNumber)

to instantiate a Dfp, then you can call .multiply or whatever on this. I thought I'd mention this because it's a bit confusing.

Option 2: GNU Scientific Library or Boost C++ Libraries. In these cases you should use JNI in order to call these native libraries.

Option 3: If you are free to use other programs and/or languages, you could consider using programs/languages for numerical computations such as Octave, Scilab, and similar.

Option 4: BigDecimal of Java.