diff --git a/R/blm_me.R b/R/blm_me.R
index ba5e865..8c2984a 100644
--- a/R/blm_me.R
+++ b/R/blm_me.R
@@ -7,7 +7,7 @@
 #' Denote \eqn{Y_i} be a binary response, \eqn{X_i} be a \eqn{q\times 1} covariate that is subject to spatial exposure measurement error,
 #' and \eqn{Z_i} be a \eqn{p\times 1} covariate without measurement error.
 #' Consider normal linear regression model,
-#' \deqn{Y_i = \beta_0 + X_i^\top \beta_x +  Z_i^\top \beta_z + \epsilon_i,\quad  \epsilon_i \stackrel{iid}{\sim} N(0, \sigma^2_Y), \quad i=1,\dots,n,}
+#' \deqn{Y_i = \beta_0 + X_i^\top \beta_X +  Z_i^\top \beta_Z + \epsilon_i,\quad  \epsilon_i \stackrel{iid}{\sim} N(0, \sigma^2_Y), \quad i=1,\dots,n,}
 #' and spatial exposure measurement error of \eqn{X_i} for \eqn{i=1,\dots,n} is incorporated into the model as a multivariate normal prior.
 #' For example when \eqn{q=1}, we have \eqn{n-}dimensional multivariate normal prior of \eqn{X = (X_1,\dots,X_n)^\top},
 #' \deqn{(X_1,\dots,X_n)\sim N_n(\mu_X, Q_X^{-1}).}
diff --git a/man/blm_me.Rd b/man/blm_me.Rd
index 1e1a8e4..b99ba3e 100644
--- a/man/blm_me.Rd
+++ b/man/blm_me.Rd
@@ -52,7 +52,7 @@ Function \code{blm_me()} runs a Gibbs sampler to carry out posterior inference;
 Denote \eqn{Y_i} be a binary response, \eqn{X_i} be a \eqn{q\times 1} covariate that is subject to spatial exposure measurement error,
 and \eqn{Z_i} be a \eqn{p\times 1} covariate without measurement error.
 Consider normal linear regression model,
-\deqn{Y_i = \beta_0 + X_i^\top \beta_x +  Z_i^\top \beta_z + \epsilon_i,\quad  \epsilon_i \stackrel{iid}{\sim} N(0, \sigma^2_Y), \quad i=1,\dots,n,}
+\deqn{Y_i = \beta_0 + X_i^\top \beta_X +  Z_i^\top \beta_Z + \epsilon_i,\quad  \epsilon_i \stackrel{iid}{\sim} N(0, \sigma^2_Y), \quad i=1,\dots,n,}
 and spatial exposure measurement error of \eqn{X_i} for \eqn{i=1,\dots,n} is incorporated into the model as a multivariate normal prior.
 For example when \eqn{q=1}, we have \eqn{n-}dimensional multivariate normal prior of \eqn{X = (X_1,\dots,X_n)^\top},
 \deqn{(X_1,\dots,X_n)\sim N_n(\mu_X, Q_X^{-1}).}