The parameter estimation methods for the nonlinear exponential autoregressive model are
investigated in this paper. We develop a forgetting factor gradient parameter estimation …

The parameter estimation methods for the nonlinear exponential autoregressive (ExpAR)
model are investigated in this work. Combining the hierarchical identification principle with …

Given its simplicity of modeling and sensitivity to condition variations, time series model is
widely used in feature extraction to realize fault classification and diagnosis. However …

This paper focuses on the recursive parameter estimation methods for the exponential
autoregressive (ExpAR) model. Applying the negative gradient search and introducing a …

This article is devoted to study the problem of estimation in the periodic restricted
exponential autoregressive EXPAR (1) models. The estimation procedure that is used is the …

It is thoroughly acknowledged that the historical financial time series is not linear, exhibits
structural changes, and is volatile. It has been noticed in the current literature that because …

This paper focuses on the recursive parameter estimation problem of the exponential
autoregressive (ExpAR) model. Applying the Newton search and multi-innovation theory, a …

This study examines the utilization of periodic exponential autoregressive (PEXPAR) models
in analyzing rainfall time series data from Algeria. The method of Gaussian quasi maximum …

This study focuses on the recursive parameter estimation problems for the non‐linear
exponential autoregressive model with moving average noise (the ExpARMA model for …

In financial modeling, the assumption of Gaussian noise, has been a classical assumption.
Models based on this assumption have been widely used in various fields due to their …