Granger causality (GC) is a widely used approach for detecting causal relations, but it struggles with nonlinearity and nonstationarity. Cross-kernel Granger causality generalizes the method using kernel functions to capture nonlinear cross-relations between variables, addressing the limitations of traditional GC in handling nonstationary processes.