R: High Dimensional Time Series Analysis Tools

# High Dimensional Time Series Analysis Tools

## Documentation for package ‘HDTSA’ version 1.0.6-2

- DESCRIPTION file

## Help Pages

BeijingAir | Beijing multi-site air pollution tensor data
Coint | Identifying the cointegration rank of nonstationary vector time series
CP_Inference | Inference for the Double Projection Iterations (DPI) factor loading estimator in the tensor time series CP-factor model
CP_MTS | Estimating the matrix time series CP-factor model
CP_TTS | Estimating the tensor time series CP-factor model
DGP.CP | Generating simulated data for the example in Chang et al. (2024)
Factors | Factor analysis for vector time series
FamaFrench | Fama-French 10*10 return series
HDSReg | Factor analysis with observed regressors for vector time series
IPindices | U.S. Industrial Production indices
MartG_test | Testing for martingale difference hypothesis in high dimension
PCA_TS | Principal component analysis for vector time series
predict.factors | Make predictions from a '"factors"' object
predict.mtscp | Make predictions from a '"mtscp"' object
predict.tspca | Make predictions from a '"tspca"' object
QWIdata | The national QWI hires data
SpecMulTest | Multiple testing with FDR control for spectral density matrix
SpecTest | Global testing for spectral density matrix
UR_test | Testing for unit roots based on sample autocovariances
WN_test | Testing for white noise hypothesis in high dimension