Description Usage Arguments Value See Also Examples
Aggregate boostrap replicates of spacemap into a final Boot.Vote model.
1 |
bfits |
List of fitted spacemap models returned from |
thresh |
Positive numeric threshold for the minimum proportion of bootstrap replicate model fits with a particular edge such that the edge is included in the Boot.Vote model. |
givenX |
Logical. Defaults to FALSE. Should be set to TRUE when
|
Returns a list of lists.
First list is bv
, which encodes the edges in two logical adjacency matrices.
yy
Adjacency matrix where 1 for the (q,l) off-diagonals element indicate an edge
between the qth and lth response variables, and 0 otherwise.
xy
Adjacency matrix where 1 for the (p,q) element indicate an edge
between the pth predictor and qth response variable, and 0 otherwise.
Second list is bdeg
, which contains the degree distribution for each bootstrap replicate fit.
yy
Integer matrix (B \times Q where the (q,b) off-diagonals element indicates
the out-degree of the qth response variable for the bth converged model based on the bth bootstrap replicate.
xy
Integer matrix (B \times P where the (p,b) element indicates
the out-degree of the pth predictor variable for the bth converged model based on the bth bootstrap replicate.
Third list is bc
, which stores several additional statistics on the ensemble network fits.
yy
Integer matrix containing the y–y edge selection frequency out of B replicates.
xy
Integer matrix containing the x–y edge selection frequency out of B replicates.
dfyy
Integer vector containing the total number of y–y edges for each fit.
dfxy
Integer vector containing the total number of x–y edges for each fit.
Note: If method == "space" & givenX == FALSE
,
then no xy, dfxy
elements will be reported in the above lists.
1 2 3 4 5 6 7 8 9 10 11 12 | #Load simulation
library(spacemap)
data(sim1)
#Boostrap Ensemble (B = 10) for illustration only
tune <- data.frame(lam1 = 70, lam2 = 28, lam3 = 17.5)
#suppress warnings because parallel backend not set up.
ens <- suppressWarnings(bootEnsemble(Y = sim1$Y, X = sim1$X, tune = tune,
method = "spacemap", B = 10))
bv <- suppressWarnings(bootVote(ens))
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