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flxzimmer · Aug 7, 2023 · 82fa628 · 82fa628
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diff --git a/README.Rmd b/README.Rmd
@@ -46,7 +46,7 @@ set.seed(1)
 
 This is a basic demonstration to the mlpwr package by going through a toy example. We want to obtain the sample size necessary for a mean comparison using an one-sample t-test. 
 
- 
+
 
 The package can be loaded via
 

diff --git a/README.md b/README.md
@@ -98,7 +98,7 @@ We can perform the search with the above arguments in use.
 ``` r
 ds <- find.design(simfun = simfun_ttest, boundaries = c(100,
     300), power = 0.95, evaluations = 4000)
-#>  Updates: 1, Evaluations: 1000, Time: 0.2 Updates: 2, Evaluations: 1200, Time: 0.2 Updates: 3, Evaluations: 1400, Time: 0.3 Updates: 4, Evaluations: 1600, Time: 0.4 Updates: 5, Evaluations: 1800, Time: 0.5 Updates: 6, Evaluations: 2000, Time: 0.5 Updates: 7, Evaluations: 2200, Time: 0.6 Updates: 8, Evaluations: 2400, Time: 0.6 Updates: 9, Evaluations: 2600, Time: 0.7 Updates: 10, Evaluations: 2800, Time: 0.8 Updates: 11, Evaluations: 3000, Time: 0.8 Updates: 12, Evaluations: 3200, Time: 0.9 Updates: 13, Evaluations: 3400, Time: 1 Updates: 14, Evaluations: 3600, Time: 1 Updates: 15, Evaluations: 3800, Time: 1.1 Updates: 16, Evaluations: 4000, Time: 1.2
+#>  Updates: 1, Evaluations: 1000, Time: 0.2 Updates: 2, Evaluations: 1200, Time: 0.3 Updates: 3, Evaluations: 1400, Time: 0.4 Updates: 4, Evaluations: 1600, Time: 0.4 Updates: 5, Evaluations: 1800, Time: 0.5 Updates: 6, Evaluations: 2000, Time: 0.6 Updates: 7, Evaluations: 2200, Time: 0.7 Updates: 8, Evaluations: 2400, Time: 0.8 Updates: 9, Evaluations: 2600, Time: 0.8 Updates: 10, Evaluations: 2800, Time: 0.9 Updates: 11, Evaluations: 3000, Time: 0.9 Updates: 12, Evaluations: 3200, Time: 1 Updates: 13, Evaluations: 3400, Time: 1.1 Updates: 14, Evaluations: 3600, Time: 1.1 Updates: 15, Evaluations: 3800, Time: 1.2 Updates: 16, Evaluations: 4000, Time: 1.3
 ```
 
 While it is running, the function gives us some updates regarding the
@@ -117,7 +117,7 @@ summary(ds)
 #> Design: N = 201
 #> 
 #> Power: 0.95064,  SE: 0.00379
-#> Evaluations: 4000,  Time: 1.29,  Updates: 16
+#> Evaluations: 4000,  Time: 1.47,  Updates: 16
 #> Surrogate: Logistic regression
 ```