define_object_for_initial_clustering_macropca: Defines the object that will be used to define a initial...

In RCTS: Clustering Time Series While Resisting Outliers

Defines the object that will be used to define a initial clustering.

Description

This is a short version of define_object_for_initial_clustering() which only contains implementations for robust macropca case and classical case.

Usage

define_object_for_initial_clustering_macropca(
  Y,
  k,
  kg,
  comfactor,
  robust,
  method_estimate_beta = "individual",
  method_estimate_factors = "macro",
  verbose = FALSE
)

Arguments

Y	Y: NxT dataframe with the panel data of interest
k	number of common factors to be estimated
kg	number of group specific factors to be estimated
comfactor	estimated common factors
robust	TRUE or FALSE: defines using the classical or robust algorithm to estimate beta
method_estimate_beta	defines how beta is estimated. Default case is an estimated beta for each individual. Default value is "individual." Possible values are "homogeneous", "group" or "individual".
method_estimate_factors	specifies the robust algorithm to estimate factors: default is "macro". The value is not used when robust is set to FALSE.
verbose	when TRUE, it prints messages

Value

matrix with N rows and 10 columns

RCTS documentation built on May 31, 2023, 9:20 p.m.