Hi there,
Thanxs for your response, it makes a lot more sense now, it seems like a simple probability problem except its a lot bigger, I now get how we get the distribution function for each step, however in terms of the initial distribution function, how do we work out such distributions? I...
Hi all,
To answer my own question, pretty much the family of random variables is the same in both Markov and Gaussian Process what's different is how the densities are calculated, Especially the Markov process its quit remarkable. In terms of understanding it graphically, we have an initial...
Hi all,
Im currently researching into stochastic proesses. The gaussian process wasnt hard to tackle, However, I don't understand the Markov process. See I understand that a stochastic process is a family of random variable's which is dependent and distinguished upon another variable. But...
Hi there,
Yeah I am pretty much focused on the maths part of it, I am going to start researching it once I get some info about it from here, let me know what you know about the topic even a global perspective or the core concepts about it would be of help.
Regards
Steven
Hi there,
of course if your looking at historical figure's then the time must be limited and therefore in a fixed time, in terms of your expectation it is suppose to be E[e^xt] this is the moment generating function which is an alternative to find the expectation to the integral x*f(x)dx. And...
Hi There,
Your sayin that, we are not in need of such a condition to satisfy the stationary concept, in actual fact we are in need of it especially when for example, let's says we are modeling the stock price historically it has been trading around $20 and then all of a sudden a stock split...
Hi all,
Im going to be researching into Stochastic processes don't know anything about it except the title, Thought I might get on here to get an introduction, see what other people know about it and tips that would be helpful in understanding the concepts? so if anybody knows anything about...
Hi There,
In terms of CASE 1:
P(green)=1/8
In Terms of CASE 2:
E1=result of the first bag
E2=result of the second bag
E3=result of the third bag
P(E1nE2nE3)=(1/8)*(1/8)*(1/8)=1/512
This should be correct, hope it helps
regards Steven
Hi all,
Im currently researching into Multivariate distributions, in particular I am trying to derive the characteristic function of the bivariate distribution of a gaussian. While knowing that a gaussian density function cannot be integrated how is it possible to find the characteristic...
hello saltydog
well the reason why Iv got straight line approximations is because I have structured my program with the 2nd order runge kutta and the second order adam bashforth and second order adam moulton, upgrading the program shouldn't be too difficult anyway
steven
hello all
to answer my original question, a predictor-corrector algorithm, consists of basically two parts, the predictor extrapolates the solution over some finite range h based on the information at prior points and is inherently unstable and the corrector which allows for this local...
Hello Saltydog
well that aint a bad idea, there is always one way of finding out how something works and that is if we demonstrated it graphically, I have been writting a program over the last few days, writting the predictor corrector code wasnt difficult but trying to plot each step all on...
hello all
so far after a bit more research I have come to understand that the adams bashforth requires information about the solution at more than one point, If I assume that we already know these points then what this method does is find an interpolating polynomial that passes through these...
hello all
I have been researching into numerical analysis, differential equations in particular, I underdstand how the Runge kutta methods work geometrically but I don't quit understand what is the idea behind Adam moultons method And Adam Bashforth method, Is there a graphical way of...