Models.dist.rank.local.mean: Create a Distance Matrix Corresponding to the Mean Ranks of...

In thomasWeise/processMineR.modelDist: An R Package for Computing Distance Matrices from Models

Description

For each model M we compute the distances to all other models. These distances are then ranked using the normalizing ranking method rank.dist. The distance of one models set to another model set is then the mean of the corresponding ranks.

Usage

Models.dist.rank.local.mean(models, distance = RegressionResult.dist.default,
  cores = 1L, logging = FALSE)

Arguments

models	the models records
distance	the RegressionResult-to-RegressionResult distance metric
cores	the number of CPU cores to use
logging	the logging setup, see makeLogger

Value

an instance of dist

See Also

Models.dist.rank.aggregate

Models.dist.rank.global.mean

thomasWeise/processMineR.modelDist documentation built on May 29, 2019, 3:18 p.m.