4 \title{Minimum Variance Reduction}
6 Phylogenetic tree construction based on the minimum variance reduction.
13 \item{X}{a distance matrix.}
14 \item{V}{a variance matrix.}
15 \item{fs}{agglomeration criterion parameter: it is coerced as an
16 integer and must at least equal to one.}
19 The MVR method can be seen as a version of BIONJ which is not
20 restricted to the Poison model of variance (Gascuel 2000).
23 an object of class \code{"phylo"}.
26 Criscuolo, A. and Gascuel, O. (2008). Fast NJ-like algorithms to deal
27 with incomplete distance matrices. \emph{BMC Bioinformatics}, 9.
29 Gascuel, O. (2000). Data model and classification by trees: the
30 minimum variance reduction (MVR) method. \emph{Journal of
31 Classification}, \bold{17}, 67--99.
33 \author{Andrei Popescu \email{niteloserpopescu@gmail.com}}
35 \code{\link{bionj}}, \code{\link{fastme}}, \code{\link{njs}},
40 rt <- dist.dna(woodmouse, variance = TRUE)
41 v <- attr(rt, "variance")