Man pages for sdim
An R Package for Supervised Dimension Reduction
| estimate_ardl_multi | Estimate ARDL(p1, p2) model |
| estimate_ar_res | Estimate AR(p) model |
| eval_factors | Evaluate extracted factors against target returns |
| grunfeld | Grunfeld (1958) investment dataset |
| he2023_dacheng202 | Dacheng 202-portfolio value-weighted returns from He, Huang,... |
| he2023_factors | Factor proxies from He, Huang, Li, Zhou (2023) |
| he2023_ff17vw | Fama-French 17-industry value-weighted portfolios from He,... |
| he2023_ff30vw | Fama-French 30-industry value-weighted portfolios from He,... |
| he2023_ff48ew | Fama-French 48-industry equal-weighted portfolios from He,... |
| he2023_ff48vw | Fama-French 48-industry value-weighted portfolios from He,... |
| he2023_ff5 | Fama-French 5-factor data from He, Huang, Li, Zhou (2023) |
| huang2022_ip | Industrial production growth from Huang, Jiang, Li, Tong,... |
| huang2022_macro | FRED-MD macro predictors from Huang, Jiang, Li, Tong, Zhou... |
| ipca_est | IPCA factor extraction |
| oos_standardize | Standardize columns to zero mean and unit variance |
| pca_est | PCA factor extraction |
| pls_est | PLS factor extraction (Matlab-faithful NIPALS algorithm) |
| predict.sdim_fit | Project new data onto estimated factor loadings |
| predict.sdim_spca | Project new data onto estimated sPCA factor loadings |
| rra_est | Reduced-Rank Approach (RRA) factor extraction |
| select_ar_lag_sic | Select AR lag order by SIC (BIC) |
| spca_est | Scaled PCA factor extraction |
