get_ith_local_neighbors: A function to obtain the local neighbors based on...
In resemble: Memory-Based Learning in Spectral Chemometrics

get_ith_local_neighbors

R Documentation

A function to obtain the local neighbors based on dissimilarity matrices from orthogonal projections.

Description

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

Usage

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,
  ...
)

Arguments

`ith_xr`	the set of neighbors of a Xu observation found in Xr
`ith_xu`	the Xu observation
`ith_yr`	the response values of the set of neighbors of the Xu observation found in Xr
`ith_yu`	the response value of the xu observation
`diss_usage`	a character string indicating if the dissimilarity data will be used as predictors ("predictors") or not ("none").
`ith_neig_indices`	a vector of the original indices of the Xr neighbors.
`k`	the number of nearest neighbors to select from the already identified neighbors
`k_diss`	the distance threshold to select the neighbors from the already identified neighbors
`k_range`	a min and max number of allowed neighbors when `k_diss` is used
`spike`	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`.
`diss_method`	the ortho_diss() method
`pc_selection`	the pc_selection argument as in ortho_diss()
`ith_group`	the vector containing the group labes of `ith_xr`.
`center`	center the data in the local diss computation?
`scale`	scale the data in the local diss computation?

Value

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