probability of Markov process

I have this tansition matrix which is a propability of Markov processpropability of Markov process

P= [ .4 .0 .0 .1 .0 .7 .3 .2 .3 .2 .3 .4 .3 .1 .4 .3 ] and the initial distribution is x (1) = [.1 .1 .5 .3]T

I would like to compute x where x = Px.

Here is my attempt but I am not getting the correct result .

Thanks in advance!

M = [.4 .0 .3 .3 ;.0 .7 .2 .1; .0 .3 .3 .4 ;.1 .2 .4 .3];
X=[.1 .1 .5 .3];
B = X.';

 eig(M');
% % ans = 
% 
%     1.0000
%     0.5357
%     0.2685
%    -0.1043

 [V,D] = eig(M');
P = V(:,1)';
P = P./sum(P);
% P =
%        0.0400    0.4400    0.2800    0.2400
% P*M
% ans =
%        .0400    0.4400    0.2800    0.2400

[Walter Roberson]

See also user question at https://www.mathworks.com/matlabcentral/answers/482001-markov-processing-and-eigenvectors

[Brave A]

All of them are my questions. Are you trying to help?

[Brave A]

Any thoughts?

[Walter Roberson]

You asked two related but seemingly different questions. Any of the volunteers who have the skills to deal with the topic might wish to consider the two questions together, or might be willing to spend a little extra time extending the solution for one to also cover the other. My making the reference to your other question makes it more likely that you will receive a response to both of your parts.

[Walter Roberson]

I would like to compute x where x = Px.

Do you mean that you would like to find x such that x = M*x ? If not then you need to define P for us.

The P you calculate at the moment is the solution for P == P*M rather than for P == M*P

[Brave A]

Thanks for your help!

sorry I didnot mentioed that

P = [ .4 .0 .0 .1 .0 .7 .3 .2 .3 .2 .3 .4 .3 .1 .4 .3 ]

and I need to find X .