This article considers model averaging in the class of the integer-valued autoregressive (INAR) processes. The INAR process is a class of structural models that can be used to model dependent count data in fields such as medicine, economics, finance and marketing. It specifies the data...

This paper proposes an adjusted-range based self-normalization method to construct confidence intervals for censored dependent data, which helps to circumvent the long-run variance estimation and tuning parameter selection problems. Simulation studies confirm the validity of this new approach