get_ith_local_neighbors: A function to obtain the local neighbors based on...

In resemble: Memory-Based Learning in Spectral Chemometrics

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: itemize

Author(s)

Leonardo Ramirez-Lopez

resemble documentation built on April 21, 2023, 1:13 a.m.