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Fix definition of primitive matrix and clarify Hamilton matrix reference #584

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4 changes: 2 additions & 2 deletions lectures/eigen_II.md
Original file line number Diff line number Diff line change
Expand Up @@ -238,7 +238,7 @@ A = \begin{bmatrix} 0.5 & 0.1 \\
\end{bmatrix}
$$

$A$ here is also a primitive matrix since $A^k$ is everywhere nonnegative for $k \in \mathbb{N}$.
$A$ here is also a primitive matrix since $A^k$ is everywhere positive for some $k \in \mathbb{N}$.
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Copilot AI Apr 23, 2025

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[nitpick] The updated definition appears correct; however, consider explicitly stating 'strictly positive' to align precisely with the standard mathematical definition of a primitive matrix.

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$A$ here is also a primitive matrix since $A^k$ is everywhere positive for some $k \in \mathbb{N}$.
$A$ here is also a primitive matrix since $A^k$ is strictly positive for some $k \in \mathbb{N}$.

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@HumphreyYang @jstac what do you think of this [nitpick] AI review?

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Many thanks @mmcky,

I think everywhere positive matches the definition of primitive matrices so I think we should keep it : )


$$
B = \begin{bmatrix} 0 & 1 \\
Expand Down Expand Up @@ -392,7 +392,7 @@ We are now prepared to bridge the languages spoken in the two lectures.

A primitive matrix is both irreducible and aperiodic.

So Perron-Frobenius theorem explains why both {ref}`Imam and Temple matrix <mc_eg3>` and [Hamilton matrix](https://en.wikipedia.org/wiki/Hamiltonian_matrix) converge to a stationary distribution, which is the Perron projection of the two matrices
So Perron-Frobenius theorem explains why both {ref}`Imam and Temple matrix <mc_eg3>` and {ref}`Hamilton matrix <mc_eg2>` converge to a stationary distribution, which is the Perron projection of the two matrices

```{code-cell} ipython3
P = np.array([[0.68, 0.12, 0.20],
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