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This dissertation develops a first-order multivariate Poisson integer-valued autoregressive (MPINAR(1)) model to improve disease outbreak detection in public health surveillance systems. The MPINAR(1) model is proposed as a computationally tractable alternative to the general multivariate...

This dissertation develops a negative binomial integer-valued generalized autoregressive conditional heteroscedastic model of order p, q (negative binomial INGARCH(p, q)) for overdispersed count time series data with potential extreme values. The model is formulated such that its conditional...