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The spectrum occupancy models widely used to date in dynamic spectrum access/cognitive radio (DSA/CR) research frequently rely on assumptions and oversimplifications that have not been validated with empirical measurement data. In this context, this paper presents an empirical time-dimension model of spectrum use that is appropriate for DSA/CR studies. Concretely, a two-state discrete-time Markov chain with novel deterministic and stochastic duty cycle models is proposed as an adequate mean to accurately describe spectrum occupancy in the time domain. The validity and accuracy of the proposed modeling approach is evaluated and corroborated with extensive empirical data from a multiband spectrum measurement campaign. The obtained results demonstrate that the proposed approach is able to accurately capture and reproduce the relevant statistical properties of spectrum use observed in real-world channels of various radio technologies. The importance of accurately modeling spectrum use in the design and evaluation of novel DSA/CR techniques is highlighted with a practical case study.