idiographic: Idiographic Network Estimation from Intensive Longitudinal Data

Person-specific and within-person network estimation from intensive longitudinal / ESM panel data: preprocessing audits (preprocess()), edge-stability diagnostics (estimate_stability()), model-comparison reports (compare_idiographic()), rolling forecast validation (validate_forecast()), rolling ordinary vector autoregression (fit_rolling_var()), rolling graphical vector autoregression (fit_rolling_graphical_var()), ordinary vector autoregression (fit_var()), graphical vector autoregression (fit_graphical_var()), multilevel vector autoregression (fit_mlvar()), unified SEM (fit_usem()), Group Iterative Multiple Model Estimation (fit_gimme()), and idiographic supervised machine-learning models (fit_ml()) for individualized prediction. Use fit_idiographic() for registry-driven dispatch or the direct fit_*() functions. Every result has tidy as.data.frame(), summary(), and print methods; network estimators also share edges(), coefs(), nodes(), matrices(), and plotting methods. equivalence() reports the exact validation scope attached to each method.

See also

Useful links:

• https://pak.dynasite.org/idiographic/

• https://github.com/mohsaqr/idiographic

• Report bugs at https://github.com/mohsaqr/idiographic/issues

Author

Maintainer: Mohammed Saqr [email protected] [copyright holder]

Authors:

• Sonsoles López-Pernas [email protected]