How to run this code for 1000 times?

1 view (last 30 days)
Eric Chua
Eric Chua on 27 May 2020
Commented: KSSV on 29 May 2020
%For C1
lambda1 = [60.21, 41.58, 9.11, 8.71, 3.83, 3.74, 18.06]
r1 = poissrnd(lambda1)
%For C2
lambda2 = [41.58, 60.21, 8.71, 9.11, 3.74, 3.83, 18.06]
r2 = poissrnd(lambda2)
%Designed training sequences x1 and x2
x1 = [1,1,1,0,0,0,0,1,0,1,0,1,1,0,0,1] ;
x2 = [1,1,1,0,1,0,0,0,1,1,1,0,0,0,0,1] ;
%X[3] to X[16]
X3 = [1 1 1 1 1 1 1]' ;
X4 = [0 0 1 1 1 1 1]' ;
X5 = [0 1 0 0 1 1 1]' ;
X6 = [0 0 0 1 0 0 1]' ;
X7 = [0 0 0 0 0 1 1]' ;
X8 = [1 0 0 0 0 0 1]' ;
X9 = [0 1 1 0 0 0 1]' ;
X10 = [1 1 0 1 1 0 1]' ;
X11 = [0 1 1 1 0 1 1]' ;
X12 = [1 0 0 1 1 1 1]' ;
X13 = [1 0 1 0 0 1 1]' ;
X14 = [0 0 1 0 1 0 1]' ;
X15 = [0 0 0 0 1 0 1]' ;
X16 = [1 1 0 0 0 0 1]' ;
%X,a 7x14 matrix
X = [X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16];
%C, a 7x2 matrix
C = [r1; r2]' ;
%Y, a 14x2 matrix
Y = X'*C ;
%Yd = Poiss(Y) (at equation (8))
Yd = poissrnd(Y)
%y1, a 14x1 matrix ; y2, a 14x1 matrix
y1 = Y(:,1)
y2 = Y(:,2)
%Least Square Estimate of C
Cls = (inv(X*X'))*(X*Yd)
% To set to zero all the negative entries of C
Cls1 = max(Cls,0)
%Mean square error of LS C and C
MSE = mean((C - Cls1).^2)
  4 Comments
Eric Chua
Eric Chua on 27 May 2020
Thanks for the reply. r1 and r2 are values that will change every single run as they are generated with poisson, and so do the C, Y, Yd.
Eric Chua
Eric Chua on 27 May 2020
Cls and Cls1 are also changing for every run.

Sign in to comment.

Accepted Answer

KSSV
KSSV on 27 May 2020
N = 1000 ;
MSE = zeros(N,2) ;
for i = 1:N
%For C1
lambda1 = [60.21, 41.58, 9.11, 8.71, 3.83, 3.74, 18.06] ;
r1 = poissrnd(lambda1) ;
%For C2
lambda2 = [41.58, 60.21, 8.71, 9.11, 3.74, 3.83, 18.06] ;
r2 = poissrnd(lambda2) ;
%Designed training sequences x1 and x2
x1 = [1,1,1,0,0,0,0,1,0,1,0,1,1,0,0,1] ;
x2 = [1,1,1,0,1,0,0,0,1,1,1,0,0,0,0,1] ;
%X[3] to X[16]
X3 = [1 1 1 1 1 1 1]' ;
X4 = [0 0 1 1 1 1 1]' ;
X5 = [0 1 0 0 1 1 1]' ;
X6 = [0 0 0 1 0 0 1]' ;
X7 = [0 0 0 0 0 1 1]' ;
X8 = [1 0 0 0 0 0 1]' ;
X9 = [0 1 1 0 0 0 1]' ;
X10 = [1 1 0 1 1 0 1]' ;
X11 = [0 1 1 1 0 1 1]' ;
X12 = [1 0 0 1 1 1 1]' ;
X13 = [1 0 1 0 0 1 1]' ;
X14 = [0 0 1 0 1 0 1]' ;
X15 = [0 0 0 0 1 0 1]' ;
X16 = [1 1 0 0 0 0 1]' ;
%X,a 7x14 matrix
X = [X3,X4,X5,X6,X7,X8,X9,X10,X11,X12,X13,X14,X15,X16];
%C, a 7x2 matrix
C = [r1; r2]' ;
%Y, a 14x2 matrix
Y = X'*C ;
%Yd = Poiss(Y) (at equation (8))
Yd = poissrnd(Y) ;
%y1, a 14x1 matrix ; y2, a 14x1 matrix
y1 = Y(:,1) ;
y2 = Y(:,2) ;
%Least Square Estimate of C
Cls = (inv(X*X'))*(X*Yd) ;
% To set to zero all the negative entries of C
Cls1 = max(Cls,0) ;
%Mean square error of LS C and C
MSE(i,:) = mean((C - Cls1).^2) ;
end
  11 Comments
Eric Chua
Eric Chua on 28 May 2020
How do I add up all the MSE value in first column and divide by 1000 to get the average?
KSSV
KSSV on 29 May 2020
Use the function mean.

Sign in to comment.

More Answers (0)

Categories

Find more on Configure Simulation Conditions in Help Center and File Exchange

Tags

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!