fix some docs

R/fcwt.R

@@ -9,12 +9,12 @@
 #'  Sampling rate of input time series in physical units.
 #'
 #' @param freq_begin
-#'  Sets the minimal frequency (`> 0`!), in same units as `sample_freq`,
+#'  Sets the minimal frequency (\code{> 0}!), in same units as \code{sample_freq},
 #'  that should be contained in the output.
 #'
 #' @param freq_end
-#'  Sets the maximal frequency (`> freq_begin`!), in sameunits as `sample_freq`,
-#'  that should be contained in the output.
+#'  Sets the maximal frequency (\code{> freq_begin}!), in same units as
+#'  \code{sample_freq}, that should be contained in the output.
 #'
 #' @param n_freqs
 #'  Number of frequency bins generated by the CWT. The frequencies
@@ -23,8 +23,7 @@
 #'
 #' @param sigma
 #'  Sets a dimensionless parameter modifying the wavelet spread which in the
-#'  time-domain is roughly given by
-#'  \eqn{\Sigma_t \sim \sqrt(2) \frac{\sigma}{f}}.
+#'  time-domain is roughly given by \eqn{\Sigma_t \sim \sqrt{2} \frac{\sigma}{f}}.
 #'  Changing this parameter adjusts the time/frequency uncertainty balance.
 #'  Defaults to 1.
 #'  Larger (lower) value of sigma corresponds to a better (worse) frequency
@@ -35,16 +34,16 @@
 #'  settings corresponding values to NA.
 #'  We define the essential support of the
 #'  (Gaußian) wavelet to be four times its standard deviation,
-#'  \eqn{4 \Sigma_t = 2 * \sqrt(2) \frac{\sigma}{f}}, and so a wavelet touches
+#'  \eqn{4 \Sigma_t = 2 * \sqrt{2} \frac{\sigma}{f}}, and so a wavelet touches
 #'  the boundary if the distance of the center of the wavelet to the boundary
-#'  is less then \eqn{4 \Sigma_t}. Values that fall into that rangeare removed
+#'  is less then \eqn{4 \Sigma_t}. Values that fall into that range are removed
 #'  if `remove_coi = TRUE`.
 #'
 #' @param nthreads
 #'  Number of threads used by the computation, if applicable.
 #'
 #' @return
-#'  A numeric real-valued matrix with `dim = c(length(signal), n_freqs)`.
+#'  A numeric real-valued matrix with \code{dim = c(length(signal), n_freqs)}.
 #'
 #' @examples
 #' ts_sin_440 <- sin((1:44100) * 2 * pi * 440 / 44100)
@@ -57,7 +56,6 @@
 #'   n_freqs = 10,
 #'   sigma = 5
 #' )
-#'
 #' @export
 fcwt <- function(signal,
                  sample_freq,