fix dox

R/Index_calculations.r

@@ -66,7 +66,7 @@
 #'   pooled populations.
 #'   
 #' @param sublist a list of character strings or integers to indicate specific 
-#'   population names (accessed via \code{\link[adegenet:Accessors]{popNames}}). 
+#'   population names (accessed via \code{popNames()}). 
 #'   Defaults to "ALL".
 #'   
 #' @param exclude a \code{vector} of population names or indexes that the user

R/bruvo.r

@@ -445,7 +445,7 @@ bruvo.boot <- function(pop, replen = 1, add = TRUE, loss = TRUE, sample = 100,
 #'   different populations containing the same multilocus genotype.}
 #'   
 #' @details The minimum spanning network generated by this function is generated
-#'   via igraph's \code{\link[igraph]{minimum.spanning.tree}}. The resultant
+#'   via igraph's \code{\link[igraph:mst]{minimum.spanning.tree}}. The resultant
 #'   graph produced can be plotted using igraph functions, or the entire object
 #'   can be plotted using the function \code{\link{plot_poppr_msn}}, which will
 #'   give the user a scale bar and the option to layout your data.

R/classes.r

@@ -86,7 +86,7 @@ setClassUnion("mlgORnumeric", c("MLG", "numeric"))
 #' @author Zhian N. Kamvar
 #' @seealso \code{\link{as.genclone}} \code{\link{as.snpclone}} 
 #'   \code{\linkS4class{genind}} \code{\linkS4class{genlight}} 
-#'   \code{\link[adegenet:Accessors]{strata}} \code{\link[adegenet:Accessors]{setPop}} 
+#'   \code{\link[adegenet:accessors]{strata}} \code{\link[adegenet:accessors]{setPop}} 
 #'   \code{\link{MLG}} \code{\link{mll}} \code{\link{mlg.filter}}
 #' @import methods
 #' @examples

R/visualizations.r

@@ -1254,7 +1254,7 @@ plot_poppr_msn <- function(x,
 #'   represent an independent sample.
 #'   
 #' @details Internally, this function works by converting the data into a 
-#'   \code{\link[pegas]{loci}} object, which represents genotypes as a data 
+#'   \code{\link[pegas:read.loci]{loci}} object, which represents genotypes as a data 
 #'   frame of factors. Random samples are taken of 1 to n-1 columns of the 
 #'   matrix and the number of unique rows are counted to determine the number of
 #'   multilocus genotypes in that random sample. This function does not take