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2391b35e42aa93fb5b9c8666a36d9044
mooc-rr
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9ed4dfd2
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9ed4dfd2
authored
Nov 08, 2025
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2391b35e42aa93fb5b9c8666a36d9044
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module2/exo1/toy_document_fr.Rmd
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9ed4dfd2
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@@ -17,6 +17,33 @@ Mon ordinateur m’indique que π vaut approximativement :
...
@@ -17,6 +17,33 @@ Mon ordinateur m’indique que π vaut approximativement :
pi
pi
#> [1] 3.141593
#> [1] 3.141593
**En utilisant la méthode des aiguilles de Buffon**
set.seed(42)
N <- 100000
x <- runif(N)
theta <- pi/2 * runif(N)
2 / (mean(x + sin(theta) > 1))
#> [1] 3.14327
**Avec un argument « fréquentiel » de surface (Méthode de Monte Carlo)**
set.seed(42)
N <- 1000
df <- data.frame(X = runif(N), Y = runif(N))
df$Accept <- (df$X^2 + df$Y^2 <= 1)
# Visualisation
library(ggplot2)
ggplot(df, aes(x = X, y = Y, color = Accept)) +
geom_point(alpha = .2) +
coord_fixed() +
theme_bw()
**d’obtenir une approximation (pas terrible) de π**
4 * mean(df$Accept)
#> [1] 3.156
```{r setup, include=FALSE}
```{r setup, include=FALSE}
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