In fact I don't think you can compute the cumulative gaussian distribution from a closed formula...
i think that a sigmoid function might be better suited than the hyperbolic tangent.... take a look at http://en.wikipedia.org/wiki/Sigmoid_function for more. I'm not at home so can't open your patch; sorry if I have the wrong idea.
Best,
Jacob
On 11/9/05, pete mcpartlan petemcpartlan@yahoo.co.uk wrote:
cdf i think, when i said flat at both ends i meant horizontal. so yeah, an s curve not a bell curve-
so yes cumulative gaussian distibution -i think...
sorry to clog up the list with my mathematic incompetency, but how do i integrate the pdf?
thanks
pete
Charles Henry wrote:
hold on...what kind of distribution are you looking for? the expression is pdf for a probability density function that flattens out at both ends. the cdf (cumulative density) is obtained by integrating the pdf-this is the stretched 's' Simulating random variables by the inversion method involves taking the integral of your chosen pdf, and putting the values in a table. Then you can pick numbers between 0 and 1 and look up the random variable's value. So, what distribution do you want?
Chuck
On 11/9/05, pete mcpartlan petemcpartlan@yahoo.co.uk wrote:
thanks Tebjan,
but...its not half a cosine because it has to flatten out at both ends.
and secondly i have no idea how to take an equation like that and implement that in pd... maybe i didnt explain that i'm not too good at all that maths stuff...
thanks,
pete
Tebjan Halm wrote:
(cos(x) + 1) * c with x inside the range -Pi to 0 and c is a constant that defines the output range of the curve 0 to c ...
sorry, the output range will be 0 to 2*c ... because the cos range -1 to 1 gets shifted upwards by the +1 to 0..2 and c scales this range ...
pete mcpartlan schrieb:
hello,
i need help with a maths problem... i am trying to plot a cumulative distribution curve to weight random. I have a [random] that feeds into a chain of [moses], sililar to the markov chain example but what i want to do is have a table dump into the right inlet of each moses changing the weighting. so far so good. what i need help with is the curve which needs to make it more likely for the next result to be near the same position. the attatched patch has an array with the sort of function it should be... like an s stetched at both ends... is there a way i can do this with expr? or am i going to have to type out a list for each state? i'm sure this is probably quite a simple maths problem... but beyond me... or other ideas? might it be simpler to have a longer array with the curve is then plotted at different points back into the array... but considering i'm probably going to have 16+ of these and other stuff i want to make it as simple as possible....
thanks in advance and apologies for rambling a bit..
pete
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