Update performance.qmd (#978)

vignettes/performance.qmd

@@ -59,11 +59,11 @@ results[, c(1, 3, 5)]
 # "slopes(mod)"                                     15.33s   26.83GB
 ```
 
-The benchmarks above were conducted using the development version of `marginaleffects` on 2023-02-03.
+The benchmarks above were conducted using the development version of `marginaleffects` on 2023-12-09.
 
 ## Speed comparison
 
-The `slopes` function is relatively fast. This simulation was conducted using the development version of the package on 2022-04-04:
+The `slopes` function is relatively fast. This simulation was conducted using the development version of the package on 2023-12-09:
 
 ```{r, eval = FALSE}
 library(margins)
@@ -109,4 +109,4 @@ results[, c(1, 3, 5)]
 
 Models estimated on larger datasets (> 1000 observations) can be impossible to process using the `margins` package, because of memory and time constraints. In contrast, `marginaleffects` can work well on much larger datasets.
 
-Note that, in some specific cases, `marginaleffects` will be considerably slower than packages like `emmeans` or `modmarg`. This is because these packages make extensive use of hard-coded analytical derivatives, or reimplement their own fast prediction functions.
+Note that, in some specific cases, `marginaleffects` will be considerably slower than packages like `emmeans` or `modmarg`. This is because these packages make extensive use of hard-coded analytical derivatives, or reimplement their own fast prediction functions.