diff --git a/.Rbuildignore b/.Rbuildignore
index ca23174..2e4ba37 100755
--- a/.Rbuildignore
+++ b/.Rbuildignore
@@ -12,3 +12,4 @@
 ^LICENSE\.md$
 TODO.md
 ^\.github$
+^CRAN-SUBMISSION$
diff --git a/CRAN-SUBMISSION b/CRAN-SUBMISSION
new file mode 100644
index 0000000..98bf3c1
--- /dev/null
+++ b/CRAN-SUBMISSION
@@ -0,0 +1,3 @@
+Version: 0.1.1
+Date: 2022-08-26 15:40:19 UTC
+SHA: a7eb4f1af54665ef1c659ca66b1a3b9dacd34b97
diff --git a/DESCRIPTION b/DESCRIPTION
index f5e96a0..806c7dc 100755
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
 Package: goffda
 Type: Package
 Title: Goodness-of-Fit Tests for Functional Data
-Version: 0.1.0
-Date: 2021-08-19
+Version: 0.1.1
+Date: 2022-08-26
 Authors@R: c(
     person(given = "Eduardo", family = "García-Portugués",
            role = c("aut", "cre"), email = "edgarcia@est-econ.uc3m.es",
@@ -39,5 +39,5 @@ LinkingTo: Rcpp, RcppArmadillo
 URL: https://github.com/egarpor/goffda
 BugReports: https://github.com/egarpor/goffda
 Encoding: UTF-8
-RoxygenNote: 7.1.1
+RoxygenNote: 7.2.0
 Roxygen: list(old_usage = TRUE)
diff --git a/NEWS.md b/NEWS.md
index ee531a7..7573a5a 100755
--- a/NEWS.md
+++ b/NEWS.md
@@ -19,3 +19,7 @@
 * Support forthcoming `Rcpp`'s STRICT_R_HEADERS.
 * Update bibliographical details for main reference.
 * Rename `r_gof2019_flmfr` to `r_gof2021_flmfr`.
+
+# goffda 0.1.1
+
+* Fix in HTML version of manual.
diff --git a/R/RcppExports.R b/R/RcppExports.R
index d2b0c8d..25ba08b 100644
--- a/R/RcppExports.R
+++ b/R/RcppExports.R
@@ -14,13 +14,12 @@
 #' expansion, such as Functional Principal Components (FPC).
 #'
 #' The PCvM statistic is defined as
-#' \deqn{\mathrm{PCvM}_{n,p,q} =
-#' c \cdot \mathrm{tr}(\hat\mathbf{E}_q' \mathbf{A}_\bullet \hat\mathbf{E}_q)}{
-#' PCvM_{n, p, q} = c * tr(\hat E_q' A_\bullet \hat E_q)
-#' }
+#' \deqn{\mathrm{PCvM}_{n,p,q} = c \cdot \mathrm{tr}(\hat{\mathbf{E}}_q'
+#' \mathbf{A}_\bullet \hat{\mathbf{E}}_q)}{PCvM_{n, p, q} =
+#' c * tr(\hat E_q' A_\bullet \hat E_q)}
 #' where
 #' \deqn{c = 2 \pi^{(p + q) / 2 - 1} / (q \Gamma(p / 2) \Gamma(q / 2) n^2),}
-#' \eqn{\hat\mathbf{E}_q}{\hat E_q} is the \eqn{n \times q}{n x q}
+#' \eqn{\hat{\mathbf{E}}_q}{\hat E_q} is the \eqn{n \times q}{n x q}
 #' matrix of multivariate residuals, and
 #' \eqn{\mathbf{A}_\bullet}{A_\bullet} is a \eqn{n \times n}{n x n}
 #' matrix whose \eqn{ij}-th element is
diff --git a/R/data.R b/R/data.R
index 160d4e0..2ab91ee 100755
--- a/R/data.R
+++ b/R/data.R
@@ -43,7 +43,7 @@
 #' (2017).
 #' @source
 #' The dataset comes from the companion data to Benatia et al. (2017), which
-#' was retrieved from the \href{https://davidbenatia.wordpress.com/research/}{
+#' was retrieved from the \href{https://www.davidbenatia.com/publication/}{
 #' first author's website}. The source of the electricity consumption data is
 #' the \href{https://www.ieso.ca/}{System operator's website}. The source
 #' of the preprocessed temperature values is the
diff --git a/R/flm_est.R b/R/flm_est.R
index 356e788..0910774 100755
--- a/R/flm_est.R
+++ b/R/flm_est.R
@@ -67,7 +67,7 @@
 #' \code{cv_nlambda} or \code{cv_parallel}, among others.
 #' @return A list with the following entries:
 #' \item{Beta_hat}{estimated \eqn{\beta}, a matrix with values
-#' \eqn{\hat\beta (s, t)} evaluated at the grid points for \code{X}
+#' \eqn{\hat\beta(s, t)} evaluated at the grid points for \code{X}
 #' and \code{Y}. Its size is \code{c(length(X$argvals), length(Y$argvals))}.}
 #' \item{Beta_hat_scores}{the matrix of coefficients of \code{Beta_hat}
 #' (resulting from projecting it into the tensor basis of \code{X_fpc} and
diff --git a/R/scenarios-fr.R b/R/scenarios-fr.R
index 3c255e8..5dded8d 100755
--- a/R/scenarios-fr.R
+++ b/R/scenarios-fr.R
@@ -754,6 +754,7 @@ r_gof2021_flmfr <- function(n, s = seq(0, 1, len = 101),
 #' the same grid as \code{error_fdata}, with the same length as
 #' \code{length(X_fdata$argvals)}.
 #' @inheritParams quadrature
+#' @param t grid points where responses are valued.
 #' @inheritParams elem-flmfr
 #' @return Functional linear model term as the integral (in \code{s}) between
 #' \code{X_fdata} and \code{beta}, as an \code{\link[fda.usc]{fdata}} object of
diff --git a/man/flm_est.Rd b/man/flm_est.Rd
index 5646a7d..0ccd8e9 100755
--- a/man/flm_est.Rd
+++ b/man/flm_est.Rd
@@ -65,7 +65,7 @@ Defaults to \code{"trapezoid"}.}
 \value{
 A list with the following entries:
 \item{Beta_hat}{estimated \eqn{\beta}, a matrix with values
-\eqn{\hat\beta (s, t)} evaluated at the grid points for \code{X}
+\eqn{\hat\beta(s, t)} evaluated at the grid points for \code{X}
 and \code{Y}. Its size is \code{c(length(X$argvals), length(Y$argvals))}.}
 \item{Beta_hat_scores}{the matrix of coefficients of \code{Beta_hat}
 (resulting from projecting it into the tensor basis of \code{X_fpc} and
diff --git a/man/flm_stat.Rd b/man/flm_stat.Rd
index 444a4b6..7c53235 100755
--- a/man/flm_stat.Rd
+++ b/man/flm_stat.Rd
@@ -48,13 +48,12 @@ the coefficients (scores) of the sample in a \eqn{p}-truncated basis
 expansion, such as Functional Principal Components (FPC).
 
 The PCvM statistic is defined as
-\deqn{\mathrm{PCvM}_{n,p,q} =
-c \cdot \mathrm{tr}(\hat\mathbf{E}_q' \mathbf{A}_\bullet \hat\mathbf{E}_q)}{
-PCvM_{n, p, q} = c * tr(\hat E_q' A_\bullet \hat E_q)
-}
+\deqn{\mathrm{PCvM}_{n,p,q} = c \cdot \mathrm{tr}(\hat{\mathbf{E}}_q'
+\mathbf{A}_\bullet \hat{\mathbf{E}}_q)}{PCvM_{n, p, q} =
+c * tr(\hat E_q' A_\bullet \hat E_q)}
 where
 \deqn{c = 2 \pi^{(p + q) / 2 - 1} / (q \Gamma(p / 2) \Gamma(q / 2) n^2),}
-\eqn{\hat\mathbf{E}_q}{\hat E_q} is the \eqn{n \times q}{n x q}
+\eqn{\hat{\mathbf{E}}_q}{\hat E_q} is the \eqn{n \times q}{n x q}
 matrix of multivariate residuals, and
 \eqn{\mathbf{A}_\bullet}{A_\bullet} is a \eqn{n \times n}{n x n}
 matrix whose \eqn{ij}-th element is
diff --git a/man/flm_term.Rd b/man/flm_term.Rd
index 301dc89..8ddaa39 100755
--- a/man/flm_term.Rd
+++ b/man/flm_term.Rd
@@ -17,7 +17,7 @@ for each grid point \eqn{s} in  \eqn{[a, b]} and \eqn{t} in \eqn{[c, d]}. If
 the same grid as \code{error_fdata}, with the same length as
 \code{length(X_fdata$argvals)}.}
 
-\item{t}{vectors with grid points where functions are valued.}
+\item{t}{grid points where responses are valued.}
 
 \item{int_rule}{quadrature rule for approximating the definite
 unidimensional integral: trapezoidal rule (\code{int_rule = "trapezoid"})
diff --git a/man/ontario.Rd b/man/ontario.Rd
index de69867..6eef669 100755
--- a/man/ontario.Rd
+++ b/man/ontario.Rd
@@ -24,7 +24,7 @@ A list with the following entries:
 }
 \source{
 The dataset comes from the companion data to Benatia et al. (2017), which
-was retrieved from the \href{https://davidbenatia.wordpress.com/research/}{
+was retrieved from the \href{https://www.davidbenatia.com/publication/}{
 first author's website}. The source of the electricity consumption data is
 the \href{https://www.ieso.ca/}{System operator's website}. The source
 of the preprocessed temperature values is the
diff --git a/src/flm_stat.cpp b/src/flm_stat.cpp
index 1b6c729..55ec293 100755
--- a/src/flm_stat.cpp
+++ b/src/flm_stat.cpp
@@ -17,13 +17,12 @@ using namespace Rcpp;
 //' expansion, such as Functional Principal Components (FPC).
 //'
 //' The PCvM statistic is defined as
-//' \deqn{\mathrm{PCvM}_{n,p,q} =
-//' c \cdot \mathrm{tr}(\hat\mathbf{E}_q' \mathbf{A}_\bullet \hat\mathbf{E}_q)}{
-//' PCvM_{n, p, q} = c * tr(\hat E_q' A_\bullet \hat E_q)
-//' }
+//' \deqn{\mathrm{PCvM}_{n,p,q} = c \cdot \mathrm{tr}(\hat{\mathbf{E}}_q'
+//' \mathbf{A}_\bullet \hat{\mathbf{E}}_q)}{PCvM_{n, p, q} =
+//' c * tr(\hat E_q' A_\bullet \hat E_q)}
 //' where
 //' \deqn{c = 2 \pi^{(p + q) / 2 - 1} / (q \Gamma(p / 2) \Gamma(q / 2) n^2),}
-//' \eqn{\hat\mathbf{E}_q}{\hat E_q} is the \eqn{n \times q}{n x q}
+//' \eqn{\hat{\mathbf{E}}_q}{\hat E_q} is the \eqn{n \times q}{n x q}
 //' matrix of multivariate residuals, and
 //' \eqn{\mathbf{A}_\bullet}{A_\bullet} is a \eqn{n \times n}{n x n}
 //' matrix whose \eqn{ij}-th element is