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ftsa (version 6.4)

MAF_multivariate: Maximum autocorrelation factors

Description

Dimension reduction via maximum autocorrelation factors

Usage

MAF_multivariate(data, threshold)

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

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

Author

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

Run this code
MAF_multivariate(data = pm_10_GR_sqrt$y, threshold = 0.85)

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