Now it always uses a split preconditioner, and the warning about too fast convergence was removed.
(file #40018)

If you look at algorithm 9.1 on Saad's book, you see that the split preconditioning for the conjugate gradient is realised at step 6. And it does not matter whether the preconditioner M is M1*M2. The only thing to do is to multiply the residual by inv(M). I see that Matlab always use a split preconditioner:
I would remove the warning about too fast convergence. And some tests do not work for me.

I removed the try...catch inside the iteration and the check of ishermitian.
I changed the stagnation criterion to norm(resvec(k+1)resvec(k)) <= eps * norm(resvec(k+1)).
I changed the use of preconditioner. Now it uses m1 and m2 as a split preconditioner. However, it still uses m1 as a left preconditioner when m2 does not exist.
(file #40010)

You can remove the try..catch inside the iteration: if the preconditioner is singular in the ## Initiation stage, the code will return. Cristiano used ishermitian only in some tests, I think you can remove from the code.
I think you should change the stagnation criterion. It is almost impossible that two consecutive iterations coincide (with ==). You should use something like norm(resvec(k+1)resvec(k)) <= eps * norm(resvec(k+1)).
I see you use a left preconditioner, while Matlab a split one.

Re: Comment #5
1. Solved by Comment #7.
2. I learned from Cristiano, and added try...catch to detect singular preconditioner matrix. Matlab checks it, too. For example (it is similar to a test from pcg of Cristiano),
Then flag = 2, which means that Matlab detected singular preconditioner matrix.
However, Matlab does not check whether A is symmetric or whether A is hermitian. Because pcg of Cristiano checks whether A is hermitian, my minres checks it.
3. I fixed it.
4. Matlab accepts complex matrix and works on it. Test code:
If allconverge = 1, then Matlab minres works for all the A and b above.
(file #40006)

Hi Nicholas,
Thank you for the test.
In Comment #8, A is symmetric but not hermitian. I think we should test for hermitian A as well. For example, I substituted A into the matlab example in Comment #1.
I tried it with my minres. It converged after 26 iterations, and the relative residual is 8.4181e011.
In addition, it failed to converge as for the test in comment #8.

re: questions from Comment #5, I'm not sure how to test 2, but I made a lousy complex A to substitute into the matlab example in Comment #1. It failed to converge, but it didn't produce any errors about complex input. Barring any other test, I'll assume A should be allowed to be complex.

Dear Marco,
I looked at formulas (5.135.16) and (7.4), but I think it is difficult to use them when there is a preconditioner matrix. Therefore, I adopted another method. I accumulated the residual in every iteration just like x, to avoid matrixvector multiplication per step.
Moreover, I used this method and formula (7.1) to calculate resveccg, i.e. the norm of r^c in Paige&Saunders. By the way, my x is x^M, and my resvec is the norm of r^M in Paige&Saunders.
(file #39988)

If you give me a few test scripts I can reply with the MATLAB output. If you brainstorm a large number of tests I could turn them into some test code blocks for you to debug against.

1. Could it be what given in formula (5.17) of Paige&Saunders?
Moreover, it seems that you compute the true residual (bA*x), which requires an additional matrixvector per step. I think you should use formulas (5.13)(5.16).
2. If by "illconditioned" you mean that octave gives the warning "matrix is singular...", I think Cristiano did something with try... catch.
You could use issymmetric. Does matlab check it? For instance, there is not such a check in pcg.
4. Does matlab accept complex matrices? Does it work with complex matrices?

There are still a lot of problems now:
 There is an output that matlab minres has but I do not know its meaning. This is resveccg. Therefore, I didn't add it as an output.
 My minres has 5 kinds of flags now, but I doubt its performance. Is there good methods to detect illconditioned matrix, when the information of this matrix is given by the form of matrix or functions which return the results of applying the inverse? And what about detecting matrix that is not sysmmetric or hermitian? Need tolerance here?
 My minres requires that if m1 and m2 both exist, then they should be both matrices or both function handles. However, in function pcg, m1 and m2 may be of different types.
 The paper I based on (matlab bases on it too according to the docummentation) says the matrix A should be real. I have not checked carefully whether it works with complex matrices, although it passed some tests.
I think maybe it is far from being a new function in Octave now, and I will continue to do the remaining work.

I uploaded a new mfile. It is different from the old one in these aspects:
 I added some tests, including the suggestion of Nicholas Jankowski, modified tests from pcg.m and some tests for hermitian but NOT positive definite matrices.
 I fixed some bugs, such as maxit and the using of preconditioner matrix.
 I deleted the errors and call print_usage(). (I am not sure whether I have done it correctly.)
 I added the description of usage.
(file #39970)

Thank you very much for your advices!
I ran the example with a slightly different code in matlab. That is, use the complete form of the outputs.
The result of relres (relative residual) and iter (iteration) is
not 49. It is strange.
For my mfile, I try to set maxit as 100. That is
Then the result is
and
Note that it converged at iteration 50 to a solution with relative residul 4.5e014.
There is a bug about using maxit in my code. I am fixing it, and I will do others that you mentioned.

Nice work. some comments:
are there any tests you could add to the end of the mfile, perhaps to verify expected input/output handling, errors, maybe verifying results as expected from the matlab examples?
I did run the example given on the referenced matlab help page
the output x is more or less equal to ones(100,1), with error on the order of 1e14.
running the same on your minres produces:
Since it's an example we can use to test algorithm compatibility, I would suggest adding the following test block to the end of the file in addition to any others to catch input/output, format, etc.
Some of your errors related to providing incorrect inputs (nargin<2 test for example) should call print_usage()
Regarding usage, I don't know how mandatory this is, but usually there's a separate line for each valid calling method. so a line for minres(A,b), then minres(A,b,tol), etc.
Last, a complete patch should also update the scripts/sparse/module.mk file, the documentation file (I guess under doc/interpreter/sparse.txi), and add the new function to /NEWS

It solves the linear system of equations A*x = b by means of the minimum residual method.
Refenrences:
1. Matlab documentation of minres
2. C. C. PAIGE and M. A. SAUNDERS, @cite{Solution of Sparse Indefinite Systems of Linear Equations},
SIAM J. Numer. Anal., 1975. (the minimum residual method)
