diff --git a/R/mc_build_sigma.R b/R/mc_build_sigma.R
index d46aa5e5b8fe853f399c2fd393941ed2eb5c7cde..3e858d92821e8605673989574f4cf881220365e7 100644
--- a/R/mc_build_sigma.R
+++ b/R/mc_build_sigma.R
@@ -30,7 +30,9 @@ mc_build_sigma <- function(mu, Ntrial = 1, tau, power, Z, sparse, variance,
             Omega <- mc_build_omega(tau = tau, Z = Z, covariance_link = covariance, sparse = sparse)
             chol_Sigma <- chol(Omega$Omega)
             inv_chol_Sigma <- solve(chol_Sigma)
-            output <- list(Sigma_chol = chol_Sigma, Sigma_chol_inv = inv_chol_Sigma, D_Sigma = Omega$D_Omega)
+            output <- list(Sigma_chol = chol_Sigma, 
+                           Sigma_chol_inv = inv_chol_Sigma, 
+                           D_Sigma = Omega$D_Omega)
         }
         if (covariance == "inverse") {
             inv_Sigma <- mc_build_omega(tau = tau, Z = Z, covariance_link = "inverse", sparse = sparse)
diff --git a/R/mc_variance_function.R b/R/mc_variance_function.R
index f6fb9a699fedf0468d230b2174689edbaf69a4ea..0d54ff4a0937c4d77cb8020cdca8f8ccdac42ec1 100644
--- a/R/mc_variance_function.R
+++ b/R/mc_variance_function.R
@@ -30,7 +30,8 @@
 #' mc_variance_function(mu = mu$mu, power = c(2,1), Ntrial = 1, variance = 'binomialPQ',
 #' inverse = FALSE, derivative_power = TRUE, derivative_mu = TRUE)
 # Generic variance function ---------------------------
-mc_variance_function <- function(mu, power, Ntrial, variance, inverse, derivative_power, derivative_mu) {
+mc_variance_function <- function(mu, power, Ntrial, variance, inverse, 
+                                 derivative_power, derivative_mu) {
     assert_that(is.logical(inverse))
     assert_that(is.logical(derivative_power))
     assert_that(is.logical(derivative_mu))