Evaluation of the performance of the Shewhart control chart
for the OIB-INAR(1) process and comparison with the performance of the
Shewhartchart for the Borel INAR(1) process
Statistical process control; ¯X chart; Integer
autoregressive processes; Inflated process of ones.
In the face of technological advances and the large
amount of information generated, count data is becoming increasingly
autocorrelated. This creates a growing need for new models and monitoring
tools that take into account the specific characteristics of this data. In this paper,
we propose a Shewhart control chart control chart for autocorrelated count data
that can be modeled by an INAR(1) process with innovations from the inflated
Borel distribution of ones (OIB-INAR(1)). This model is suitable for modeling
data with inflation of ones, underdispersion, equidispersion or overdispersion.
We will also compare the performance of this graph with that of a process Borel
INAR(1), which models series of counts truncated at zero, also with
underdispersion, equidispersion or overdispersion. Borel INAR(1) can be seen
as a particular case of the OIB-INAR(1). The performance 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 upper
control limit (UCL) and the evaluation of the performance of the graphs are
carried out through computational studies using Monte Carlo simulations. To
illustrate the applicability of the proposed method, we present an example with
real data.