New ideas for summer 2023!!!

[symiin]

1. Automating individual model fitting
2. Automating VAR
3. Automating leave-one out model fitting and getting residuals for construction of diagnostic statistics
4. Extending dynr.taste to work with dynr.formula for nonlinear discrete-time dynamic models (Meng’s IMPS – Compare dynr.taste to Laura Bringmann’s pointwise IC approach for detecting “outliers”)
5. Extending dynr.taste to work with dynr.formula for nonlinear continuous-time dynamic models
6. Getting reliability discrete-time models
7. Getting reliability for continuous-time models
8. Monte Carlo CIs for different models – starting with the VAR model (Jek)
9. Power analysis (dynr.aperitiv)
10. Mixture dynamic analysis
    emxStateSpaceMixtureModel
    https://search.r-project.org/CRAN/refmans/EasyMx/html/emxStateSpaceMixtureModel.html
    https://osf.io/9zwfd
    https://osf.io/p82bv
11. Specifying covariance function as formula