# Residual analysis of cross-sectional time-series forecasts

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?

• I don't get what you mean by 'autocorrelation of residuals across the cross-section'. Can you clarify? – Vishal Belsare Sep 16 '12 at 11:15