diff --git a/DESCRIPTION b/DESCRIPTION
index 823cb30..d71d898 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -34,4 +34,4 @@ LazyData: yes
 VignetteBuilder: 
   knitr,
   R.rsp
-RoxygenNote: 6.0.1
+RoxygenNote: 6.1.0
diff --git a/man/gen_multilevel.Rd b/man/gen_multilevel.Rd
index 5c4ec93..fdd8886 100644
--- a/man/gen_multilevel.Rd
+++ b/man/gen_multilevel.Rd
@@ -4,8 +4,9 @@
 \alias{gen_multilevel}
 \title{Generate simulated data for multilevel models}
 \usage{
-gen_multilevel(n = 25, m = 6, sigma_e = 2, sigma_u0 = 2, sigma_u1 = 2,
-  sigma_u01 = -2, beta0 = 0, beta1 = 2, x.jitter = 0.5, seed = NULL)
+gen_multilevel(n = 25, m = 6, sigma_e = 2, sigma_u0 = 2,
+  sigma_u1 = 2, sigma_u01 = -2, beta0 = 0, beta1 = 2,
+  x.jitter = 0.5, seed = NULL)
 }
 \arguments{
 \item{n}{Sample size. Input either a single number for a balanced data set,
diff --git a/man/gen_smooth.Rd b/man/gen_smooth.Rd
index 4d4aa52..68110a3 100644
--- a/man/gen_smooth.Rd
+++ b/man/gen_smooth.Rd
@@ -4,7 +4,8 @@
 \alias{gen_smooth}
 \title{Generate simulated data for smoothing models}
 \usage{
-gen_smooth(n = 150, xlim = c(0.2, 4.6), x.jitter = 0.65, seed = NULL)
+gen_smooth(n = 150, xlim = c(0.2, 4.6), x.jitter = 0.65,
+  seed = NULL)
 }
 \arguments{
 \item{n}{Sample size.}
diff --git a/man/iprior.Rd b/man/iprior.Rd
index 9f5e1a9..05b73b4 100644
--- a/man/iprior.Rd
+++ b/man/iprior.Rd
@@ -12,17 +12,18 @@
   control = list(), interactions = NULL, est.lambda = TRUE,
   est.hurst = FALSE, est.lengthscale = FALSE, est.offset = FALSE,
   est.psi = TRUE, fixed.hyp = NULL, lambda = 1, psi = 1,
-  nystrom = FALSE, nys.seed = NULL, model = list(), train.samp, test.samp)
-
-\method{iprior}{formula}(formula, data, kernel = "linear", one.lam = FALSE,
-  method = "direct", control = list(), est.lambda = TRUE,
-  est.hurst = FALSE, est.lengthscale = FALSE, est.offset = FALSE,
-  est.psi = TRUE, fixed.hyp = NULL, lambda = 1, psi = 1,
-  nystrom = FALSE, nys.seed = NULL, model = list(), train.samp, test.samp,
-  ...)
-
-\method{iprior}{ipriorKernel}(object, method = "direct", control = list(),
-  ...)
+  nystrom = FALSE, nys.seed = NULL, model = list(), train.samp,
+  test.samp)
+
+\method{iprior}{formula}(formula, data, kernel = "linear",
+  one.lam = FALSE, method = "direct", control = list(),
+  est.lambda = TRUE, est.hurst = FALSE, est.lengthscale = FALSE,
+  est.offset = FALSE, est.psi = TRUE, fixed.hyp = NULL, lambda = 1,
+  psi = 1, nystrom = FALSE, nys.seed = NULL, model = list(),
+  train.samp, test.samp, ...)
+
+\method{iprior}{ipriorKernel}(object, method = "direct",
+  control = list(), ...)
 
 \method{iprior}{ipriorMod}(object, method = NULL, control = list(),
   iter.update = 100, ...)
diff --git a/man/iprior_cv.Rd b/man/iprior_cv.Rd
index bec2301..81a1452 100644
--- a/man/iprior_cv.Rd
+++ b/man/iprior_cv.Rd
@@ -14,10 +14,11 @@
   nys.seed = NULL)
 
 \method{iprior_cv}{formula}(formula, data, folds = 2, one.lam = FALSE,
-  par.cv = TRUE, kernel = "linear", method = "direct", control = list(),
-  est.lambda = TRUE, est.hurst = FALSE, est.lengthscale = FALSE,
-  est.offset = FALSE, est.psi = TRUE, fixed.hyp = NULL, lambda = 1,
-  psi = 1, nystrom = FALSE, nys.seed = NULL, ...)
+  par.cv = TRUE, kernel = "linear", method = "direct",
+  control = list(), est.lambda = TRUE, est.hurst = FALSE,
+  est.lengthscale = FALSE, est.offset = FALSE, est.psi = TRUE,
+  fixed.hyp = NULL, lambda = 1, psi = 1, nystrom = FALSE,
+  nys.seed = NULL, ...)
 }
 \arguments{
 \item{y}{Vector of response variables}
diff --git a/man/kernL.Rd b/man/kernL.Rd
index e968a23..875aeff 100644
--- a/man/kernL.Rd
+++ b/man/kernL.Rd
@@ -5,16 +5,17 @@
 \alias{kernL.formula}
 \title{Load the kernel matrices for I-prior models}
 \usage{
-kernL(y, ..., kernel = "linear", interactions = NULL, est.lambda = TRUE,
-  est.hurst = FALSE, est.lengthscale = FALSE, est.offset = FALSE,
-  est.psi = TRUE, fixed.hyp = NULL, lambda = 1, psi = 1,
-  nystrom = FALSE, nys.seed = NULL, model = list(), train.samp, test.samp)
-
-\method{kernL}{formula}(formula, data, kernel = "linear", one.lam = FALSE,
+kernL(y, ..., kernel = "linear", interactions = NULL,
   est.lambda = TRUE, est.hurst = FALSE, est.lengthscale = FALSE,
   est.offset = FALSE, est.psi = TRUE, fixed.hyp = NULL, lambda = 1,
-  psi = 1, nystrom = FALSE, nys.seed = NULL, model = list(), train.samp,
-  test.samp, ...)
+  psi = 1, nystrom = FALSE, nys.seed = NULL, model = list(),
+  train.samp, test.samp)
+
+\method{kernL}{formula}(formula, data, kernel = "linear",
+  one.lam = FALSE, est.lambda = TRUE, est.hurst = FALSE,
+  est.lengthscale = FALSE, est.offset = FALSE, est.psi = TRUE,
+  fixed.hyp = NULL, lambda = 1, psi = 1, nystrom = FALSE,
+  nys.seed = NULL, model = list(), train.samp, test.samp, ...)
 }
 \arguments{
 \item{y}{Vector of response variables}
diff --git a/man/predict.Rd b/man/predict.Rd
index e2dc7b1..167da05 100644
--- a/man/predict.Rd
+++ b/man/predict.Rd
@@ -7,7 +7,8 @@
 \alias{print.ipriorPredict}
 \title{Obtain predicted values from \code{ipriorMod} objects}
 \usage{
-\method{fitted}{ipriorMod}(object, intervals = FALSE, alpha = 0.05, ...)
+\method{fitted}{ipriorMod}(object, intervals = FALSE, alpha = 0.05,
+  ...)
 
 \method{predict}{ipriorMod}(object, newdata = list(), y.test = NULL,
   intervals = FALSE, alpha = 0.05, ...)
diff --git a/man/summary.ipriorMod.Rd b/man/summary.ipriorMod.Rd
index 8276ea5..d85293d 100644
--- a/man/summary.ipriorMod.Rd
+++ b/man/summary.ipriorMod.Rd
@@ -3,7 +3,6 @@
 \name{summary.ipriorMod}
 \alias{summary.ipriorMod}
 \alias{print.ipriorMod}
-\alias{summary.ipriorMod}
 \title{Print and summary method for I-prior models}
 \usage{
 \method{print}{ipriorMod}(x, digits = 5, ...)