Provides model-agnostic visual diagnostics for vector autoregressive (VAR) models. Given empirical data, model predictions, residuals, and optionally simulated data, the package assembles a multi-panel diagnostic grid: empirical vs. predicted time series, residual inspection, residuals vs. predictions scatter, and posterior predictive style checks via simulated trajectories. Output is a 'patchwork' object composed of 'ggplot2' plots, allowing further customisation via standard 'ggplot2' theme calls. Follows the approach described in Haslbeck et al. (2026) &lt;<a href="https://doi.org/10.31234%2Fosf.io%2Fk6uz4_v3" target="_top">doi:10.31234/osf.io/k6uz4_v3</a>&gt;.

Provides model-agnostic visual diagnostics for vector autoregressive (VAR) models. Given empirical data, model predictions, residuals, and optionally simulated data, the package assembles a multi-panel diagnostic grid: empirical vs. predicted time series, residual inspection, residuals vs. predictions scatter, and posterior predictive style checks via simulated trajectories. Output is a 'patchwork' object composed of 'ggplot2' plots, allowing further customisation via standard 'ggplot2' theme calls. Follows the approach described in Haslbeck et al. (2026) &lt;<a href="https://doi.org/10.31234%2Fosf.io%2Fk6uz4_v3" target="_top">doi:10.31234/osf.io/k6uz4_v3</a>&gt;.