MAF_multivariate: Maximum autocorrelation factors

In ftsa: Functional Time Series Analysis

Maximum autocorrelation factors

Description

Dimension reduction via maximum autocorrelation factors

Usage

MAF_multivariate(data, threshold)

Arguments

data	A p by n data matrix, where p denotes the number of variables and n denotes the sample size
threshold	A threshold level for retaining the optimal number of factors

Value

MAF	Maximum autocorrelation factor scores
MAF_loading	Maximum autocorrelation factors
Z	Standardized original data
recon	Reconstruction via maximum autocorrelation factors
recon_err	Reconstruction errors between the standardized original data and reconstruction via maximum autocorrelation factors
ncomp_threshold	Number of maximum autocorrelation factors selected by explaining autocorrelation at and above a given level of threshold
ncomp_eigen_ratio	Number of maximum autocorrelation factors selected by eigenvalue ratio tests

Author(s)

Han Lin Shang

References

M. A. Haugen, B. Rajaratnam and P. Switzer (2015). Extracting common time trends from concurrent time series: Maximum autocorrelation factors with applications, arXiv paper https://arxiv.org/abs/1502.01073.

See Also

ftsm

Examples

MAF_multivariate(data = pm_10_GR_sqrt$y, threshold = 0.85)

ftsa documentation built on Sept. 11, 2023, 5:09 p.m.