estimate_algorithm: This function is a wrapper around the initialization and the...

In eh-in-r/RCTS: Clustering Time Series While Resisting Outliers

This function is a wrapper around the initialization and the estimation part of the algorithm, for one configuration. It is only used for the serialized algorithm.

Description

This function is a wrapper around the initialization and the estimation part of the algorithm, for one configuration. It is only used for the serialized algorithm.

Usage

estimate_algorithm(Y, X, S, k, kg, maxit = 30, robust = TRUE)

Arguments

Y	Y: NxT dataframe with the panel data of interest
X	X: NxTxp array containing the observable variables
S	number of estimated groups
k	number of common factors to be estimated
kg	number of group specific factors to be estimated
maxit	maximum limit for the number of iterations
robust	TRUE or FALSE: defines using the classical or robust algorithm to estimate beta

Value

list with

1. estimated beta

2. vector with group membership

3. matrix with the common factor(s) (contains zero's if there are none estimated)

4. loadings to the common factor(s)

5. list with the group specific factors for each of the groups

6. data.frame with loadings to the group specific factors augmented with group membership and id (to have the order of the time series)

Examples

set.seed(1)
original_data <- create_data_dgp2(60, 30)
Y <- original_data[[1]]
X <- original_data[[2]]
estimate_algorithm(Y, X, 3, 0, c(3,3,3), maxit = 2, robust = TRUE)

eh-in-r/RCTS documentation built on May 19, 2023, 1:09 p.m.