path_weights {PairViz} | R Documentation |
These functions perform calculations on edge matrices containing pairwise information.
path_weights(edgew, path, symmetric = TRUE,edge.index=edge_index(edgew),...) path_cis(edgew, path,edge.index=edge_index(edgew)) edge2dist(edgew, edge.index=edge_index(edgew)) dist2edge(d) edge_index(x, order="default")
edgew |
A Matrix (or vector) whose ith row (or element) has weights for pair indexed by pair in row i of edge.index.
For edge2dist , edgew should be a vector. |
path |
Vector of indices into rows of edgew . |
symmetric |
If TRUE edge weights are interpreted as symmetric. |
edge.index |
A 2-column matrix with each row giving indices for
corresponding weight in edgew . |
d |
A dist or matrx of distances. |
order |
If "low.order.first" or "scagdf", lists lowest index pairs first, otherwise lists pairs starting with 1, then 2 etc. |
x |
An edgew matrix or vector, or a positive integer. |
... |
path_weights
- Returns matrix of path weights so that the ith row of result contains weights for indices path[i], path[i+1]
path_cis
- Returns matrix of path confidence intervals so that the ith row of result contains intervals for mean-path[i] - mean-path[i+1]
edge2dist
- Returns a dist
,
containing elements of edgew
.
dist2edge
- Returns a vector of edge weights.
edge_index
-A generic function. Returns a 2-column matrix with one row for
each edge. Each row contains an index pair i,j. If order
is "low.order.first" or "scagdf", lists lowest index pairs first - this is the default ordering for class scagdf
, otherwise lists pairs
starting with 1, then 2 etc
nnodes
- Here edgew
contains edge weights for a complete graph; returns the number of nodes in this complete graph.
C.B. Hurley and R.W. Oldford
see overview
require(PairViz) s <- matrix(1:40,nrow=10,ncol=4) edge2dist(s[,1]) path_weights(s,1:4) path_weights(s,eseq(5)) fm1 <- aov(breaks ~ wool + tension, data = warpbreaks) tuk <- TukeyHSD(fm1, "tension")[[1]] # Here the first argument (weight matrix) can have number of columns path_weights(tuk,c(1:3,1)) # Here the first argument (weight matrix) should have an odd number of columns- # the first is the mean difference, other column pairs are endpoints of CIs path_cis(tuk[,-4],c(1:3,1))