On First Order Autoregressive Asymmetric Logistic Process

An additive first order autoregressive model with logistic distribution as marginal is studied. We have obtained a representation of the innovation random variable using stable random variable. In order to model asymmetric data, we have introduced asymmetric logistic distribution and first-order autoregressive asymmetric logistic process. We discussed some important properties of the processes. Model parameters are estimated by least square and Gaussian methods. We conducted a simulation study for checking the accuracy of the parameter estimation methods. As an application, we modelled population growth time series data using the proposed models.