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
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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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