diff --git a/R/smoothArea.R b/R/smoothArea.R
index 7fd14f3..a3ff7c5 100644
--- a/R/smoothArea.R
+++ b/R/smoothArea.R
@@ -391,8 +391,8 @@ plot.svysae <- function(x, return_list = F, plot.factor = NULL, ...) {
   }
 }
 
-#' Plot heatmap comparing pairwise posterior exceedence probabilities for all
-#' areas
+#' Plot heatmap comparing pairwise posterior exceedence probabilities for svysae object
+#' 
 #'
 #' @param x svysae object. Plots are created for all models in this object.
 #' @param posterior.sample Matrix of posteriors samples of area level quantities with one row for each area and one column for each sample. This argument may be specified to only provide a heatmap for the desired samples.
@@ -405,6 +405,7 @@ plot.svysae <- function(x, return_list = F, plot.factor = NULL, ...) {
 #' \dontrun{
 #' data(DemoData2)
 #' data(DemoMap2)
+#' library(survey)
 #' des0 <- svydesign(ids = ~clustid+id, strata = ~strata,
 #'                   weights = ~weights, data = DemoData2, nest = T)
 #' Xmat <- aggregate(age~region, data = DemoData2, FUN = mean)
@@ -500,7 +501,7 @@ compareEstimates <- function(x,
     suppressWarnings(print(g_heat))
   }
 }
-#' Title
+#' Mapping estimates for svysae object
 #'
 #' 
 #' @param x syvsae object
diff --git a/R/smoothUnit.R b/R/smoothUnit.R
index 5b6d244..4b27653 100644
--- a/R/smoothUnit.R
+++ b/R/smoothUnit.R
@@ -26,15 +26,16 @@
 #' \dontrun{
 #' data(DemoData2)
 #' data(DemoMap2)
+#' library(survey)
 #' des0 <- svydesign(ids = ~clustid+id, strata = ~strata,
 #'                  weights = ~weights, data = DemoData2, nest = T)
 #'                  
-#' EXAMPLE 1: Continuous response model
+#' # EXAMPLE 1: Continuous response model
 #' cts.res <- smoothUnit(formula = tobacco.use ~ 1,
 #'                       domain = ~region,
 #'                       design = des0, X.pop = DemoData2)
 #'                       
-#' EXAMPLE 2: Binary response model
+#' # EXAMPLE 2: Binary response model
 #' bin.res <- smoothUnit(formula = tobacco.use ~ 1,
 #'                       family = "binomial",
 #'                       domain = ~region,
diff --git a/man/compareEstimates.Rd b/man/compareEstimates.Rd
index 6e22243..8cc800c 100644
--- a/man/compareEstimates.Rd
+++ b/man/compareEstimates.Rd
@@ -2,8 +2,7 @@
 % Please edit documentation in R/smoothArea.R
 \name{compareEstimates}
 \alias{compareEstimates}
-\title{Plot heatmap comparing pairwise posterior exceedence probabilities for all
-areas}
+\title{Plot heatmap comparing pairwise posterior exceedence probabilities for svysae object}
 \usage{
 compareEstimates(x, posterior.sample = NULL)
 }
@@ -16,13 +15,13 @@ compareEstimates(x, posterior.sample = NULL)
 ggplot containing heat map of pairwise comparisons
 }
 \description{
-Plot heatmap comparing pairwise posterior exceedence probabilities for all
-areas
+Plot heatmap comparing pairwise posterior exceedence probabilities for svysae object
 }
 \examples{
 \dontrun{
 data(DemoData2)
 data(DemoMap2)
+library(survey)
 des0 <- svydesign(ids = ~clustid+id, strata = ~strata,
                   weights = ~weights, data = DemoData2, nest = T)
 Xmat <- aggregate(age~region, data = DemoData2, FUN = mean)
diff --git a/man/mapEstimates.Rd b/man/mapEstimates.Rd
index ea75d36..77bc4f5 100644
--- a/man/mapEstimates.Rd
+++ b/man/mapEstimates.Rd
@@ -2,7 +2,7 @@
 % Please edit documentation in R/smoothArea.R
 \name{mapEstimates}
 \alias{mapEstimates}
-\title{Title}
+\title{Mapping estimates for svysae object}
 \usage{
 mapEstimates(x, geo.data, variable, viridis.option = "viridis")
 }
@@ -19,7 +19,7 @@ mapEstimates(x, geo.data, variable, viridis.option = "viridis")
 ggplot containing map of small area posterior summary statistics
 }
 \description{
-Title
+Mapping estimates for svysae object
 }
 \examples{
 \dontrun{
diff --git a/man/smoothArea.Rd b/man/smoothArea.Rd
index 6f74509..42bd35f 100644
--- a/man/smoothArea.Rd
+++ b/man/smoothArea.Rd
@@ -68,11 +68,12 @@ area level model
 \dontrun{
 data(DemoData2)
 data(DemoMap2)
+library(survey)
 des0 <- svydesign(ids = ~clustid+id, strata = ~strata,
                   weights = ~weights, data = DemoData2, nest = T)
 Xmat <- aggregate(age~region, data = DemoData2, FUN = mean)
 
-EXAMPLE 1: Continuous response model
+# EXAMPLE 1: Continuous response model
 cts.res <- smoothArea(tobacco.use ~ 1,
                       domain = ~region,
                       design = des0,
@@ -82,7 +83,7 @@ cts.res <- smoothArea(tobacco.use ~ 1,
                       pc.u.phi = 0.5,
                       pc.alpha.phi = 2/3)
 
-EXAMPLE 2: Including area level covariates
+# EXAMPLE 2: Including area level covariates
 cts.cov.res <- smoothArea(tobacco.use ~ age, 
                           domain = ~region,
                           design = des0,
@@ -93,7 +94,7 @@ cts.cov.res <- smoothArea(tobacco.use ~ age,
                           pc.u.phi = 0.5,
                           pc.alpha.phi = 2/3)
 
-EXAMPLE 3: Binary response model
+# EXAMPLE 3: Binary response model
 bin.res <- smoothArea(tobacco.use ~ 1, 
                       domain = ~region,
                       design = des0,
@@ -104,7 +105,7 @@ bin.res <- smoothArea(tobacco.use ~ 1,
                       pc.u.phi = 0.5,
                       pc.alpha.phi = 2/3)
 
-EXAMPLE 4: Including area level covariates in binary response model
+# EXAMPLE 4: Including area level covariates in binary response model
 bin.cov.res <- smoothArea(tobacco.use ~ age, 
                           domain = ~region,
                           design = des0,
diff --git a/man/smoothUnit.Rd b/man/smoothUnit.Rd
index d91b72b..fa47810 100644
--- a/man/smoothUnit.Rd
+++ b/man/smoothUnit.Rd
@@ -61,15 +61,16 @@ unit level model
 \dontrun{
 data(DemoData2)
 data(DemoMap2)
+library(survey)
 des0 <- svydesign(ids = ~clustid+id, strata = ~strata,
                  weights = ~weights, data = DemoData2, nest = T)
                  
-EXAMPLE 1: Continuous response model
+# EXAMPLE 1: Continuous response model
 cts.res <- smoothUnit(formula = tobacco.use ~ 1,
                       domain = ~region,
                       design = des0, X.pop = DemoData2)
                       
-EXAMPLE 2: Binary response model
+# EXAMPLE 2: Binary response model
 bin.res <- smoothUnit(formula = tobacco.use ~ 1,
                       family = "binomial",
                       domain = ~region,