Abstract
In this paper, we develop an autoregressive process of order one, assuming that the innovation random variable has a Lindley distribution. The key properties of the process are investigated. Five distinct estimation techniques are used to estimate the parameters and simulation studies are conducted. The stationarity of the process is tested using a unit root test. The application of the proposed process to the analysis of time series data is demonstrated using real data sets. Based on some important statistical measures, the analysis of the data sets reveals that the proposed model fits well, and the errors are independent and Lindley-distributed.
Published Version
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