diff --git a/vignettes/articles/Jitter.Rmd b/vignettes/articles/Jitter.Rmd
index c58f8e6..f4308c2 100644
--- a/vignettes/articles/Jitter.Rmd
+++ b/vignettes/articles/Jitter.Rmd
@@ -51,8 +51,8 @@ r4ss::run(dir = dir_jitter, exe = "ss3", verbose = FALSE)
 ## Jitter 
 For this example, we will run 50 jitters. The `jitter()` function automates the entire process so you only need to give it a few arguments and it will run and produce the total likelihoods for each run. 
 
-```{r}
-Njitter <- 50 
+```{r run-jitter}
+Njitter <- 5 
 jit.likes <- r4ss::jitter(dir = dir_jitter, 
                           Njitter = Njitter, 
                           init_values_src = 1, 
@@ -92,7 +92,7 @@ converged_ssb <- jit_summary$SpawnBio %>%
   pivot_longer(col = c(1:(Njitter+1)), names_to = "jitter", values_to = "SSB") %>% 
   pivot_wider(names_from = Yr, values_from = SSB) %>% 
   mutate(rownumber = seq(1, nrow(.))) %>% 
-  column_to_rownames("jitter") %>% 
+  tibble::column_to_rownames("jitter") %>% 
   filter_at(vars(1:(ncol(.)-1)), all_vars((.) < 2 & (.) > 0.5)) %>% #keep only 
   select(rownumber) %>% 
   pull(rownumber)
diff --git a/vignettes/articles/Retrospective-Analysis.Rmd b/vignettes/articles/Retrospective-Analysis.Rmd
index 23cb349..a8c4259 100644
--- a/vignettes/articles/Retrospective-Analysis.Rmd
+++ b/vignettes/articles/Retrospective-Analysis.Rmd
@@ -42,14 +42,14 @@ file.copy(from ="../../inst/extdata/ss", to = dir_retro)
 You will need to make sure you have the [SS executable](https://github.com/nmfs-stock-synthesis/stock-synthesis) file either in your path or in the directory you are running the retrospective from (in this case `dir_retro`). An easy way to get the latest release of stock synthesis is to use the `r4ss` function `get_ss3_exe()`.
 
 ```{r}
-r4ss::get_ss3_exe(dir = dir_jitter, version = "v3.30.21")
+r4ss::get_ss3_exe(dir = dir_retro, version = "v3.30.21")
 ```
 
 ## Retrospective Analysis
 Once you have the 4 input files and SS executable, you can run retrospective analysis as shown below. We are running it for 5 1-year peels, so with each run, the last year of data is removed and the model is re-run for a total of 5 times. The number of year peels can be adjusted with the `years` argument. If the SS executable file you are using is named something other than "ss" (e.g. ss_opt_win.exe), you will need to specify this with the argument `exe = "ss_opt_win"`. 
 
 ```{r message=FALSE}
-r4ss::retro(dir = dir_retro, exe = "ss3", years = 0:-5, verbose = FALSE)
+r4ss::retro(dir = dir_retro, exe = "ss3.exe", years = 0:-5, verbose = FALSE)
 
 ```
 ## Visualizing Output 
diff --git a/vignettes/articles/likelihood.Rmd b/vignettes/articles/likelihood.Rmd
index 5135007..6c00a60 100644
--- a/vignettes/articles/likelihood.Rmd
+++ b/vignettes/articles/likelihood.Rmd
@@ -33,16 +33,10 @@ list.files(files_path)
 file.copy(from = list.files(files_path, full.names = TRUE), to = dir_tmp)
 ```
 
-```{r eval=FALSE, echo=FALSE, results = FALSE}
-file.copy(from ="../../inst/extdata/ss", to = dir_tmp)
-file.copy(from ="../../inst/extdata/ss", to = dir_profile)
-```
-
-
 You will need to make sure you have the [SS executable](https://github.com/nmfs-stock-synthesis/stock-synthesis) file either in your path or in the directory you are running the profile from (in this case `dir_profile`). An easy way to get the latest release of stock synthesis is to use the `r4ss` function `get_ss3_exe()`.
 
 ```{r}
-r4ss::get_ss3_exe(dir = dir_jitter, version = "v3.30.21")
+r4ss::get_ss3_exe(dir = dir_tmp, version = "v3.30.21")
 ```
 
 ## R0 Profile  
@@ -83,7 +77,7 @@ profile(dir = dir_profile,
         string = "SR_LN", 
         profilevec = r0_vec, 
         exe = "ss3",
-        verbose = FALSE)
+        verbose = TRUE)
 ```
 
 ## Visualizing Output