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This paper presents a frame-level hybrid framework for modeling H.264 and MPEG-4 multi-layer variable bit rate (VBR) video traffic. In this work, the base layer is modeled using a combination of wavelet and time-domain methods and the enhancement layer is linearly predicted from the base layer using the cross-layer correlation. Unlike previous studies, we analyze and successfully model both inter-GOP and intra-GOP correlation in VBR sequences. To accurately capture long-range dependent (LRD) and short-range dependent (SRD) properties of VBR traffic, we use wavelets to model the distribution of I-frame sizes and a simple time-domain model for P/B frame sizes. Simulation results demonstrate that our model effectively preserves the temporal burstiness and captures important statistical features (e.g., the autocorrelation function and the frame-size distribution) of original traffic. We also show that our model has better performance than the previous methods in both single and multi-layer sequences.