## 84 Reputation

17 years, 258 days

## Iterative process...

Maple

Hi,

I need to solve iteratively the following equation: Y=A(t) *B(Y) using the values of the following two sets .

A=[0.9,0.75,0.6,0.2,0.08,0.06,0.051,0.05]

## LambertW...

Maple

Dear all,

Im solving the following equation: V=I(t) * Z (V)

I substitute I and Z with the corresponding equations and I solve for V :

V:=solve(V=(1.027*exp(-t/0.282)+0.051*exp(1/t+(1.766*10^90))))*(2.433*10^3*exp(-0.008*V)+780),V):

and maple solves nicely  it using LambertW and i can plot V for a range of t.

I want to do the same but instead of the equations of I=f(t) and Z=f(V) to use straight the values from tables like:

## Plotting 3D...

Maple
Hi, Sorry but i ve repeated the same question a few days ago but because it was quite down the line i thought to give it another shot I would like to make a 3D plot of some density functions(F(X)) where each lets say cdf, corresponds to a time value.So far Ive tried using the transform((x, y) command.The example below where I show how I have worked out for 4 cdfs corresponding to 10,20,30 and 40 ms, hopefully it will make it clearer of what i mean.(I have a thousand of different distributions up to 10 secs). with(stats): > C001:=plot(statevalf[cdf,lognormal[0.3792,0.9556]], 0..4, colour=green):

## Defining distribution...

Maple
Hi, I have a lognormal distribution of which I know the 5% ,50% and 95% value of X.Can I work out the equation of pdf and cdf for the particular distribution? Thanks in advance, Nasos

## Mirroring Probabilities...

Maple
Hi, I have three equations Y=f(t) with each equation corresponding to a probability as shown below. Y1=f(t) with probability of 0.05% Y2=f(t) with probability of 5% and Y3=f(t) with probability of 50% If we assume that these probabilities belong to a normal distribution how can I work out the equations for 99.95% and 95%probability.In other words I would like to mirror Y1 and Y2. The idea is to plot all the equations of 0.05%,5%,50%,95% and 99.95% probability in the same plot and create a 3D surface where the axis will be Y,t and P(probability) or even better generate the equation of P=f(Y,t) that will describe this surface.
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