Hi!
How to fit a distribution is clear, in dfittool for example. An example is a gas at a fixed temperature T. A priori, the distribution of Vx velocities of its molecules is proportional to exp(-mVx^2/2kT). If I know the velocity Vx of every molecule, I will fit normal distribution to data containind Vx and will obtain normal fit with zero mean and standard deviation proportional to T (variance kT/m).
But how to fit a distribution whose parameters depend on other parameters??? An example - a gas in a volume in a gravity field with gas temperature depending on height T(z). Now every molecule has its own height z, and my data look like (Vx,z). Do I have a function to feed such data to it? I mean, to fit a normal distribution exp(-mVx^2/2kT(z)) to data, getting in the result T(z)?
The question is related to another distribution and another system, I used normal and gas as an example. The question is more general whether distribution fitting and curve fitting can be done at one step.
