Have a look at Boost Graph as it will simplify all your graph work. I am unsure if there is a Markov Chain algiorithm (I am looking for one too) but it should be easy to write once you have the graph -- a concurrent monte carlo approach maybe?
Numerical Recipes has many algorithm and code in both C and C++.
The graphviz tools are all you need to draw graphs.
As described in Numerical Recipes, the determinant is simply the product of the diagonal elements after an LU decomposition. (This book is available online, and has code for computing the LU decomposition).
On many platforms (such as any modern x86-compatible), many of the maths functions are implemented directly in the floating-point hardware (see for example http://en.wikipedia.org/wiki/X86_instruction_listings#x87_floating-point_instructions). Not all of them are used, though (as I learnt through comments to other answers here). But, for instance, the sqrt library function is often implemented directly in terms of the SSE hardware instruction.
Have a look at Boost Graph as it will simplify all your graph work. I am unsure if there is a Markov Chain algiorithm (I am looking for one too) but it should be easy to write once you have the graph -- a concurrent monte carlo approach maybe?
Numerical Recipes has many algorithm and code in both C and C++.
The graphviz tools are all you need to draw graphs.
As described in Numerical Recipes, the determinant is simply the product of the diagonal elements after an LU decomposition. (This book is available online, and has code for computing the LU decomposition).
Method of Least Squares http://en.wikipedia.org/wiki/Least_squares. This book Numerical Recipes 3rd Edition: The Art of Scientific Computing (Hardcover) has all you need for algorithms to implement Least Squares and other techniques.
I think it's a very bad idea to calculate two very large numbers and hope that the quotient comes out as something sensible.
Start by taking the natural log:
You can use
gammaln()
for the two function values, simplify, then takeexp()
to get the result you want:Numerical Recipes has a nice chapter on how to implement functions like
gammln().
On many platforms (such as any modern x86-compatible), many of the maths functions are implemented directly in the floating-point hardware (see for example http://en.wikipedia.org/wiki/X86_instruction_listings#x87_floating-point_instructions). Not all of them are used, though (as I learnt through comments to other answers here). But, for instance, the
sqrt
library function is often implemented directly in terms of the SSE hardware instruction.For some ideas on how the underlying algorithms work, you might try reading Numerical Recipes, which is available as PDFs somewhere.