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06-26-2020
03:54 AM

06-26-2020
03:54 AM

See please the attach - Prime 6.

Why in case 1 we have rank = 4

but in case 2 we have rank = 5?

Solved! Go to Solution.

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06-26-2020
04:44 AM

06-26-2020
04:44 AM

The theorem syas:

"A system of linear equations with *n* variables has a solution if and only if the rank of its coefficient matrix *A* is equal to the rank of its augmented matrix [*A*|*b*].^{[1]} If there are solutions, they form an affine subspace of R n {\displaystyle \mathbb {R} ^{n}}

of dimension *n* − rank(*A*). In particular:

- if
*n*= rank(*A*), the solution is unique, - otherwise there are infinitely many solutions."

In your both your cases the rank of the matrix and the augmented matrix are the same. But in case1 that rank is 4, unequal to the number of equations, so there are infinitely many solutions.

In the second case you picked one solution, so the rank equals the number of equations.

The discrepancy is probably caused by the larger difference in X and Y values for the second case 2. I guess in case 1 you loose precision due to the large numbers all close together.

The numeric rank function is limited by numeric precision. I get this from the symbolic processor:

What does the symbolic processor in Prime say about the rank?

Success!

Luc

6 REPLIES 6

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06-26-2020
04:44 AM

06-26-2020
04:44 AM

The theorem syas:

"A system of linear equations with *n* variables has a solution if and only if the rank of its coefficient matrix *A* is equal to the rank of its augmented matrix [*A*|*b*].^{[1]} If there are solutions, they form an affine subspace of R n {\displaystyle \mathbb {R} ^{n}}

of dimension *n* − rank(*A*). In particular:

- if
*n*= rank(*A*), the solution is unique, - otherwise there are infinitely many solutions."

In your both your cases the rank of the matrix and the augmented matrix are the same. But in case1 that rank is 4, unequal to the number of equations, so there are infinitely many solutions.

In the second case you picked one solution, so the rank equals the number of equations.

The discrepancy is probably caused by the larger difference in X and Y values for the second case 2. I guess in case 1 you loose precision due to the large numbers all close together.

The numeric rank function is limited by numeric precision. I get this from the symbolic processor:

What does the symbolic processor in Prime say about the rank?

Success!

Luc

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06-26-2020
05:13 AM

06-26-2020
05:13 AM

Re: Rouché–Capelli theorem

**Thanks, Luc!**

**I have forgot about symbolic solution!**

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06-26-2020
06:25 AM

06-26-2020
06:25 AM

Re: Rouché–Capelli theorem

I think this proves my guess:

Luc

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06-27-2020
10:13 AM

06-27-2020
10:13 AM

Re: Rouché–Capelli theorem

**SLAE with 5 unknowns and 7 equation - I have been waiting for an answer already half a day. Do I still have to wait? **

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06-27-2020
11:31 AM

06-27-2020
11:31 AM

Re: Rouché–Capelli theorem

I thought you know by now that Prime is slow.

Luc

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06-27-2020
01:25 PM