my.knn: K-nearest neighbors smoother

In joshuadhigbee/myAppliedMetrics: What the Package Does (One Line, Title Case)

Description

For multiple metrics - Euclidean and Mahalanobis Written for data.table arguments.

Usage

my.knn(
  Yvar,
  Xvars,
  read_data,
  predict_data,
  metric = "mahalanobis",
  tolerance = 1e-16,
  K = 1L
)

Arguments

Yvar	Dependent variable
Xvars	Character vector of control variables
read_data	Of type data.table - source of data
predict_data	Of type data.table - points for prediction
metric	Metric for comparison
tolerance	Tolerance level for matrix inversion
K	number of neighbors

Examples

my.knn()

joshuadhigbee/myAppliedMetrics documentation built on March 19, 2021, 3:45 p.m.