Performance evaluation of the Shewhart control chart for the Borel INAR(1) and OIB-INAR(1) processes
Statistical process control; X¯ chart; Integer autoregressive processes; inflated ones.
This paper highlights the importance of monitoring autocorrelated count data.
We propose a Shewhart control chart for autocorrelated count data that can be
modeled by an INAR(1) process with innovations from the one-inflated Borel
distribution (OIB-INAR(1)). This model is suitable for cope with data
characterized by inflation of ones, equidispersion, underdispersion and
overdispersion. In addition, we will compare the performance of this graph with
that of a Borel INAR(1) process. Borel INAR(1) process, suitable for data
truncated at zero with equidispersion, overdispersion and underdispersion,
since Borel INAR(1) can be seen as a particular case of OIB-INAR(1). The
performance evaluation of the proposed approach is based on the average
number of samples required to detect an alarm (ARL0 and ARL1) in different
scenarios. The determination of the control limits (UCL) and the evaluation of
the performance of the graphs are carried out by means of computational
studies using Monte Carlo simulations. In addition, to demonstrate the
applicability of the proposed method we present an example with real data.