Update prob distributions

This commit is contained in:
Andrew Cumming 2023-09-25 08:20:04 -04:00
parent baebd59c6d
commit 6b5dcc2a79
2 changed files with 4 additions and 4 deletions

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@ -87,12 +87,12 @@ $$0\leq u \leq \sqrt{f\left({v\over u}\right)}$$
In this method, $f(x)$ doesn't need to be normalized, only the shape of the function is needed. This method was introduced by [Kinderman and Monahan 1977](https://dl.acm.org/doi/pdf/10.1145/355744.355750). In this method, $f(x)$ doesn't need to be normalized, only the shape of the function is needed. This method was introduced by [Kinderman and Monahan 1977](https://dl.acm.org/doi/pdf/10.1145/355744.355750).
Again note how this method allows us to access the range $x=0$ to $\infty$, since the ratio $v/u\rightarrow \infty$ for $u\rightarrow 0$. Again note how this method allows us to access the range $x=0$ to $\infty$, since the ratio $v/u\rightarrow \infty$ for $u\rightarrow 0$.
```{admonition} Exercise: ```{admonition} Exercise 1
Implement these three methods for the exponential distribution and check that they work by comparing a histogram of your $x$ values with the analytic function. Implement these three methods for the exponential distribution and check that they work by comparing a histogram of your $x$ values with the analytic function.
``` ```
```{admonition} Exercise: ```{admonition} Exercise 2
Try implementing one of the following: Try implementing one of the following:
- Lorentzian distribution using transformation method - Lorentzian distribution using transformation method

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@ -5,7 +5,7 @@
"id": "6d46a72f", "id": "6d46a72f",
"metadata": {}, "metadata": {},
"source": [ "source": [
"# Sampling probability distributions Part 1" "# Probability distributions Exercise 1"
] ]
}, },
{ {
@ -260,7 +260,7 @@
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