Family of High-Ordered Integer-Valued Auto-Regressive Models and Applications

Family of High-Ordered Integer-Valued Auto-Regressive Models and Applications

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Erscheint vorauss. 10. März 2026
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This book tackles the complexities of integer-valued time series analysis, focusing on over-dispersion, excess zeros, and non-stationarity. It explores high-ordered INAR(p) models with diverse thinning mechanisms and innovation distributions, finding CML superior for inference. Addressing periodicity, harmonic functions are introduced for COVID-19 data. Novel BINAR(1) models with BPWE and SPWE innovations are applied to stock transactions, while new BPGL and SPGL bivariate distributions analyse crime data. The book derives methodologies, tests performance via simulation, and provides real-life...