Hi, obviously a very simple question, but not for me: I plot 3 graphes into one plot by : plot1 := plot(pts, x = 0 .. 5, y = 0 .. 1000, style = line, color = red); plot2 := plot(pts2, x = 0 .. 5, y = 0 .. 1000, style = line, color = blue); plot3 := plot(pts3, x = 0 .. 5, y = 0 .. 1000, style = line, color = green); G := textplot({[1, 1, "function"], [.5, .75, "derivative"]}); display(plot1, plot2, plot3) I tried to use texplot to lable the achses but it did not work. Is there another way to do it?

Hi experts, I am producing a List X[n]. After that I just want to plot the values X[n] := [n, P[n]] with n on the x axw and P[n] on the y axe. for i from .1 by .1 to 5 do n := n+1; P[n] := (i*2+3*i^2) X[n] := [n, P[n]] end do; X[1] Unfortunately I get the error message and an empty plot: Warning, unable to evaluate the function to numeric values in the region; see the plotting command's help page to ensure the calling sequence is correct

Hi experts, I generate two random variables R1 and R2 R1 := random[normald[mu[1], sigma[1]]](1000); R2 := random[normald[mu[2], sigma[2]]](1000); Now I want just the positive numbers of it and save them under K1:=R1^+ K2:=R2^+ Thanks for your help! Regards, Marc

Dear experts, I use a procedure called Powell. The result of the procedure are the 5 values below. I want to save those results in another variable called MS, but only the second and third value. > Powell(f, Xmin0); [-411.761866103766574, [17.6242885977129257, 82.3757114023303752], 10, 110] -> MS:=(17.62,82.37) The second problem is that I want to put Powell into a double loop. Just for understanding: --> N=1 till 10 M=1 till 10 Powell(f, Xmin0); End M; End N; So that I get 100 values of MS:=(....,....). That I want to save in a matrix.

Hello, I am currently using Nelder Mead for an optimization problem. I used the following code taken out of the Maple Library (www.maplesoft.com/applications/app_center_view.aspx?CID=1&SCID=18&AID=1198) Concerning this code I have 2 questions: 1. The optimized values I get are sometimes negative. My solution should be limited on positive optimization values. I am not sure how to implement this. 2. The optimization is running quite slowly. Any suggestions how to improve the running time? Here are the most important parts of the code: