The analysis and modeling of categorical time series requires quantifying the extent of dispersion and serial dependence. The dispersion of categorical data is commonly measured by Gini index or entropy, but also the recently proposed extropy measure can be used for this purpose. Regarding...

Kategoriale (nominale) Zeitreihen treten in den verschiedensten Bereichen der Praxis auf, wie der Informatik, der Biologie, der Sprachwissenschaft, u.Ä. Trotz ihrer praktischen Relevanz gibt es keine Monographien, welche die verschiedenen Aspekte bei der Analyse kategorialer Zeitreihen...

In forecasting count processes, practitioners often ignore the discreteness of counts and compute forecasts based on Gaussian approximations instead. For both central and non-central point forecasts, and for various types of count processes, the performance of such approximate point forecasts is...

Integer-valued autoregressive (INAR) time series form a very useful class of processes suitable to model time series of counts. In the common formulation of Du and Li (1991,JTSA), INAR models of order p share the autocorrelation structure with classical autoregressive time series. This fact...