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`@@ -19,6 +19,14 @@ kernelspec:`
`19`	`19`	```{index} single: Vector Autoregression; and Kalman filter
`20`	`20`	```
`21`	`21`
	`22`	`+In addition to what's in Anaconda, this lecture will need the following libraries:`
	`23`	`+`
	`24`	+```{code-cell} ipython3
	`25`	`+:tags: [hide-output]`
	`26`	`+`
	`27`	`+!pip install quantecon`
	`28`	+```
	`29`	`+`
`22`	`30`	`## Overview`
`23`	`31`
`24`	`32`	`This lecture derives the Kalman filter for a linear Gaussian state space system`

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`@@ -26,6 +26,14 @@ kernelspec:`
`26`	`26`	`:depth: 2`
`27`	`27`	```
`28`	`28`
	`29`	`+In addition to what's in Anaconda, this lecture will need the following libraries:`
	`30`	`+`
	`31`	+```{code-cell} ipython3
	`32`	`+:tags: [hide-output]`
	`33`	`+`
	`34`	`+!pip install quantecon`
	`35`	+```
	`36`	`+`
`29`	`37`	`## Overview`
`30`	`38`
`31`	`39`	`This lecture extends our analysis of likelihood ratio processes to Vector Autoregressions (VARs).`

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`@@ -23,6 +23,13 @@ kernelspec:`
`23`	`23`	`:depth: 2`
`24`	`24`	```
`25`	`25`
	`26`	`+In addition to what's in Anaconda, this lecture will need the following libraries:`
	`27`	`+`
	`28`	+```{code-cell} python3
	`29`	`+:tags: [hide-output]`
	`30`	`+`
	`31`	`+!pip install quantecon`
	`32`	+```
`26`	`33`
`27`	`34`	`## Overview`
`28`	`35`

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`@@ -26,6 +26,13 @@ kernelspec:`
`26`	`26`	`:depth: 2`
`27`	`27`	```
`28`	`28`
	`29`	`+In addition to what's in Anaconda, this lecture will need the following libraries:`
	`30`	`+`
	`31`	+```{code-cell} python3
	`32`	`+:tags: [hide-output]`
	`33`	`+`
	`34`	`+!pip install quantecon jax`
	`35`	+```
`29`	`36`
`30`	`37`	`## Overview`
`31`	`38`

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