Hi,
I was involved in a similar debate on a different project, and we came to the
conclusion that (double -> double) methods in Java should return NaN in the
case of invalid arguments, rather than throw Exceptions.
Our reasoning was by analogy with how IEEE 754 floating-point exceptions are
Hello all,
(I tried to send this yesterday, but it looks like my message bounced,
as I received some weird errors; apologies if you are receiving a
duplicate of this message.)
I have created a pull request with a new univariate finite difference
framework for [math]. The main features of this
Hello all,
I have created a pull request with a new univariate finite difference
framework for [math]. The main features of this framework are:
1. *Exact* calculation of the coefficients for any stencil type
(forward, backward, central), derivative order, and accuracy order.
This is done by
Hi,
We use CM in an options analytics package. Some of the interesting usages are:
1. Implied vol calculations (a semi-fancy root find over function with
no closed forms).
2. Dividend projections.
3. Option greeks (partial derivatives of value function), both
automatic and numerical.
4.
);
gradientAtXpls = derivativeAt(x_copy);
x[j] = xtemp;
for(int i=0;in;i++){
hessian[i][j] = (gradientAtXpls[i]-gradientAtX[i])/stepSize;
}
}
return hessian;
}
On 8/11/2011 5:36 PM, Luc Maisonobe wrote:
Le 11/08/2011 23:27, Fran Lattanzio a écrit :
Hello,
Hi Fran,
I have a proposal
Hello,
I have a proposal for a numerical derivatives framework for Commons
Math. I'd like to add the ability to take any UnivariateRealFunction
and produce another function that represents it's derivative for an
arbitrary order. Basically, I'm saying add a factory-like interface
that looks
