diff --git a/man/as.rimg.Rd b/man/as.rimg.Rd
index 04207317..ecd5b452 100644
--- a/man/as.rimg.Rd
+++ b/man/as.rimg.Rd
@@ -32,12 +32,13 @@ to an \code{rimg} object.
 \examples{
 
 # Generate some fake image data
-fake <- array(c(
-  as.matrix(rep(c(0.2, 0.4, 0.6), each = 250)),
-  as.matrix(rep(c(0.4, 0.7, 0.8), each = 250)),
-  as.matrix(rep(c(0.6, 0.1, 0.2), each = 250))
-),
-dim = c(750, 750, 3)
+fake <- array(
+  c(
+    as.matrix(rep(c(0.2, 0.4, 0.6), each = 250)),
+    as.matrix(rep(c(0.4, 0.7, 0.8), each = 250)),
+    as.matrix(rep(c(0.6, 0.1, 0.2), each = 250))
+  ),
+  dim = c(750, 750, 3)
 )
 
 # Inspect it
diff --git a/man/jnd2xyz.Rd b/man/jnd2xyz.Rd
index d7e78481..429e1428 100644
--- a/man/jnd2xyz.Rd
+++ b/man/jnd2xyz.Rd
@@ -54,7 +54,7 @@ perceptually-corrected (i.e. noise-weighted Euclidean distances)
 data(flowers)
 
 # Estimate quantum catches visual phenotype of a Blue Tit
-vis.flowers <- vismodel(flowers, visual = 'bluetit')
+vis.flowers <- vismodel(flowers, visual = "bluetit")
 
 # Estimate noise-weighted colour distances between all flowers
 cd.flowers <- coldist(vis.flowers)
diff --git a/man/jndplot.Rd b/man/jndplot.Rd
index 06144acc..3d44f7ac 100644
--- a/man/jndplot.Rd
+++ b/man/jndplot.Rd
@@ -74,7 +74,7 @@ argument, in which case they cannot be interpreted as described.
 data(flowers)
 
 # Estimate quantum catches visual phenotype of a Blue Tit
-vis.flowers <- vismodel(flowers, visual = 'bluetit')
+vis.flowers <- vismodel(flowers, visual = "bluetit")
 
 # Estimate noise-weighted colour distances between all flowers
 cd.flowers <- coldist(vis.flowers)
diff --git a/man/jndrot.Rd b/man/jndrot.Rd
index 029e106b..af150b1e 100644
--- a/man/jndrot.Rd
+++ b/man/jndrot.Rd
@@ -46,7 +46,7 @@ Rotate Cartesian coordinates obtained from \code{\link[=jnd2xyz]{jnd2xyz()}}
 data(flowers)
 
 # Estimate quantum catches visual phenotype of a Blue Tit
-vis.flowers <- vismodel(flowers, visual = 'bluetit')
+vis.flowers <- vismodel(flowers, visual = "bluetit")
 
 # Estimate noise-weighted colour distances between all flowers
 cd.flowers <- coldist(vis.flowers)
diff --git a/man/simulate_spec.Rd b/man/simulate_spec.Rd
index 263e8c24..e12e663f 100644
--- a/man/simulate_spec.Rd
+++ b/man/simulate_spec.Rd
@@ -77,29 +77,31 @@ reflect5 <- simulate_spec(wl_inflect = 575, wl_peak = c(340, 430), width_gauss =
 
 # Simulate a set of Gaussian reflectance curves with peaks varying between 400-600nm
 # in increments of 10, then combine into a single rspec object, and plot the result
-peaks <- seq(400, 600, 10)  # Peak locations
-reflectances <- lapply(seq_along(peaks), function(x) simulate_spec(wl_peak = peaks[x]))  # Simulate
-reflectances <- Reduce(merge, reflectances)  # Combine
-plot(reflectances)  # Plot
+peaks <- seq(400, 600, 10) # Peak locations
+reflectances <- lapply(seq_along(peaks), function(x) simulate_spec(wl_peak = peaks[x])) # Simulate
+reflectances <- Reduce(merge, reflectances) # Combine
+plot(reflectances) # Plot
 
 # Simulate a set of Gaussian reflectance curves with a single peak at 500 nm, but
 # with maximum reflectance varying from 30 to 90\% in 10\% increments, then combine
 # into a single rspec object, and plot the result
-ymax <- lapply(seq(30, 90, 10), function(x) c(0, x))  # Varying reflectance maxima
-reflectances2 <- lapply(ymax, function(x) simulate_spec(wl_peak = 500, ylim = x))  # Simulate
-reflectances2 <- Reduce(merge, reflectances2)  # Combine
-plot(reflectances2)  # Plot
+ymax <- lapply(seq(30, 90, 10), function(x) c(0, x)) # Varying reflectance maxima
+reflectances2 <- lapply(ymax, function(x) simulate_spec(wl_peak = 500, ylim = x)) # Simulate
+reflectances2 <- Reduce(merge, reflectances2) # Combine
+plot(reflectances2) # Plot
 
 # To simulate non-reflectance spectra (like irradiances or radiances), it's often useful
 # to explore more 'extreme' parameters. Here's a simple example which simulates
 # natural daylight, as represented by the D65 standard daylight spectrum.
-D65_real <- procspec(sensdata(illum = 'D65'), opt = 'smooth')  # Official D65 daylight spectrum
-D65_sim <- simulate_spec(wl_peak = 400,
-                         width_gauss = 1300,
-                         skew_gauss = 10,
-                         ylim = c(0, 1))  # Simulated D65
-cor.test(D65_real$D65, D65_sim$spec_p400)  # >0.99 correlation
-plot(merge(D65_real, D65_sim), lty = 1:2, ylab = 'Irradiance (\%)')  # Merge and plot the two spectra
+D65_real <- procspec(sensdata(illum = "D65"), opt = "smooth") # Official D65 daylight spectrum
+D65_sim <- simulate_spec(
+  wl_peak = 400,
+  width_gauss = 1300,
+  skew_gauss = 10,
+  ylim = c(0, 1)
+) # Simulated D65
+cor.test(D65_real$D65, D65_sim$spec_p400) # >0.99 correlation
+plot(merge(D65_real, D65_sim), lty = 1:2, ylab = "Irradiance (\%)") # Merge and plot the two spectra
 
 }
 \references{