I have forecasts and actuals for panel data (i.e. time-series cross-sectional data). The forecasts are already generated and provided by some source outside of R. I'd like to evaluate the quality of the forecasts.
Are there standard tools in R that perform various diagnostics on the residuals? By diagnostics I mean tests such as:
- auto-correlation of residuals across the cross-section
- auto-correlation of residuals along the time series for a given member
- tests for fixed effects vs. random effects
- heteroskedasticity, etc.
Or is the best way to perform these diagnostics to perhaps build a panel model using the forecast as the predictor in the panel model?