internal function. This function is used to obtain the local neighbors based on dissimilarity matrices from orthogonal projections. These neighbors are obatin from an orthogonal projection on a set of precomputed neighbors. This function is used internally by the mbl fucntion. ortho_diss(, .local = TRUE) operates in the same way, however for mbl, it is more efficient to do the re-search of the neighbors inside its main for loop
get_ith_local_neighbors(
ith_xr,
ith_xu,
ith_yr,
ith_yu = NULL,
diss_usage = "none",
ith_neig_indices,
k = NULL,
k_diss = NULL,
k_range = NULL,
spike = NULL,
diss_method,
pc_selection,
ith_group = NULL,
center,
scale,
...
)a list:
ith_xr: the new Xr data of the neighbors for the ith observation (if
diss_usage = "predictors", this data is combined with the local
dissmilarity scores of the neighbors of Xu)
ith_yr: the new Yr data of the neighbors for the ith observation
ith_xu: the ith Xu observation (if diss_usage = "predictors",
this data is combined with the local dissmilarity scores to its Xr neighbors
ith_yu: the ith Yu observation
ith_neigh_diss: the new dissimilarity scores of the neighbors for the ith observation
ith_group: the group labels for the new ith_xr
n_k: the number of neighbors
ith_components: the number of components used
the set of neighbors of a Xu observation found in Xr
the Xu observation
the response values of the set of neighbors of the Xu observation found in Xr
the response value of the xu observation
a character string indicating if the dissimilarity data will be used as predictors ("predictors") or not ("none").
a vector of the original indices of the Xr neighbors.
the number of nearest neighbors to select from the already identified neighbors
the distance threshold to select the neighbors from the already identified neighbors
a min and max number of allowed neighbors when k_diss
is used
a vector with the indices of the observations forced to be
retained as neighbors. They have to be present in all the neighborhoods and
at the top of neighbor_indices.
the ortho_diss() method
the pc_selection argument as in ortho_diss()
the vector containing the group labes of ith_xr.
center the data in the local diss computation?
scale the data in the local diss computation?
Leonardo Ramirez-Lopez