@@ -28,8 +28,6 @@ In addition to what's in Anaconda, this lecture will need the following librarie
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28 | 28 | !pip install quantecon |
29 | 29 | ``` |
30 | 30 | |
31 | | -In this lecture we will begin with the foundational concepts in spectral theory. |
32 | | - |
33 | 31 | Then we will explore the Perron-Frobenius Theorem and connect it to applications in Markov chains and networks. |
34 | 32 | |
35 | 33 | We will use the following imports: |
@@ -389,7 +387,7 @@ We are now prepared to bridge the languages spoken in the two lectures.
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389 | 387 | |
390 | 388 | A primitive matrix is both irreducible and aperiodic. |
391 | 389 | |
392 | | -So Perron-Frobenius Theorem explains why both Imam and Temple matrix and [Hamilton matrix](https://en.wikipedia.org/wiki/Hamiltonian_matrix) converge to a stationary distribution, which is the Perron projection of the two matrices |
| 390 | +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 |
393 | 391 | |
394 | 392 | ```{code-cell} ipython3 |
395 | 393 | P = np.array([[0.68, 0.12, 0.20], |
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