designmatrices: Function that creates the design matrices necessary for the...

In BNPTSclust: A Bayesian Nonparametric Algorithm for Time Series Clustering

Description

Function that generates the design matrices of the clustering algorithm based on the parameters that the user wants to consider, i.e. level, polinomial trend and/or seasonal components. It also returns the number of parameters that are considered and not considered for clustering.

Usage

designmatrices(level, trend, seasonality, deg, T, n, fun)

Arguments

level	Variable that indicates if the level of the time series will be considered for clustering. If level = 0, then it is omitted. If level = 1, then it is taken into account.
trend	Variable that indicates if the polinomial trend of the model will be considered for clustering. If trend = 0, then it is omitted. If trend = 1, then it is taken into account.
seasonality	Variable that indicates if the seasonal components of the model will be considered for clustering. If seasonality = 0, then they are omitted. If seasonality = 1, then they are taken into account.
deg	Degree of the polinomial trend of the model.
T	Number of periods of the time series.
n	Number of time series.
fun	Clustering function being used.

Value

Z	Design matrix of the parameters not considered for clustering.
X	Design matrix of the parameters considered for clustering.
p	Number of parameters not considered for clustering.
d	Number of parameters considered for clustering.

Note

For internal use.

Author(s)

Martell-Juarez, D.A.

BNPTSclust documentation built on Aug. 20, 2019, 1:04 a.m.