NEWS

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sdim 0.1.0.9000

• Reworded the package title to comply with CRAN policy (no longer starts with "An R Package for...").

sdim 0.1.0 (2026-07-11)

• Initial CRAN release.
• Five factor extraction methods for asset pricing and macroeconomic forecasting:
  • Principal Component Analysis (pca_est())
  • Partial Least Squares (pls_est())
  • Scaled PCA (spca_est()), Huang, Jiang, Li, Tong, and Zhou (2022) doi:10.1287/mnsc.2021.4020
  • Reduced-Rank Approach (rra_est()), He, Huang, Li, and Zhou (2023) doi:10.1287/mnsc.2022.4563
  • Instrumented PCA (ipca_est()), Kelly, Pruitt, and Su (2019) doi:10.1016/j.jfineco.2019.05.001
• Unified sdim_fit() wrapper with print(), summary(), plot(), and predict() methods.
• Factor evaluation utility (eval_factors()) reporting R-squared, trace R-squared, and canonical correlations against benchmark factors.
• Out-of-sample forecasting helpers: oos_standardize(), select_ar_lag_sic(), estimate_ar_res(), estimate_ardl_multi().
• Bundled datasets replicating results from the source papers: grunfeld, he2023_factors, he2023_ff17vw, he2023_ff30vw, he2023_ff48vw, he2023_ff48ew, he2023_ff5, he2023_dacheng202, huang2022_ip, huang2022_macro.
• Four vignettes: package overview, Huang et al. (2022) Table 4 replication, He et al. (2023) Table 3 replication, and IPCA on the Grunfeld panel.