Perhaps this type of question is not very suitable for this forum, but I'll try to make my question a little useful.
I'm studying stochastic processes, more precisely, Levy processes. A Levy process $X=(X_t)_{t\geq 0}$ is characterized by its characteristic function given by: $$\log \varphi_{X_t}(u)= t\left(ib'u+ \frac{u'a u}{2} + \int_{\mathbb R^d - \{0\}} \left[ e^{i u'x} - 1 - i u'x \mathbf{1}_{(|x|\leq 1)} \right] \nu(dx)\right)$$ More precisely, the whole process is characterized by the triple $(a,b, \nu)$.
A good but extremely technical book is Lévy Processes and Stochastic Calculus. However, I am interested in estimating the triple $(a,b, \nu)$. Note that the drift $b\in\mathbb R^d$ and the matrix $a$ are finite dimensional parameters and, consequently, could be estimated with parametric techniques. On the other hand, the Levy measure $\nu$ might require non-parametric techniques.
So I'm looking for bibliographical references that help me in the computational part and implementation of the estimation of $(a,b, \nu)$.
The first chapter of book Lévy Matters IV looks like a good book to me, but it's the only decent reference I've found. Also, maybe it's not as suitable for someone who doesn't have a lot of experience in the subject. So I would like to have suggestions for books with a more practical approach and, perhaps, using some language (R, python or some other).
Can you help me?
