Ding, "Least squares based iterative algorithm for pseudo-linear autoregressive moving average
systems using the data filtering technique," Journal of the Franklin Institute, vol.
Two time series statistical models were used: autoregressive model (AR) and autoregressive moving average
The latter model is called an autoregressive moving average
of order (p,q), denoted by ARMA (p,q), and is given by
We used a type of autoregressive moving average
(ARMA) model, which adjusts for confounding variables such as sewage release events and season, to look for an association between daily visits and rainfall after a defined lag.
He uses econometric examples involving practical policy issues in order to discuss production function and regression methods; univariate time series analysis; bivariate time series analysis including stochastic diffusion and cointegration; utility theory and empirical implications; vector models for multivariate problems; simultaneous equation models; limited dependent variable models; dynamic optimization and empirical analysis of consumer behavior; single, double, and maximum entropy bootstrap and inference; generalized least squares, vector autoregressive moving average
models, and estimating functions; and nonlinear models and projection pursuit regression.
We have, however identified the actual structure of the mean equation (whether it is autoregressive (AR), moving average (MA) or autoregressive moving average
(ARMA)) based on historical stock return data.
The important class of models for which dth difference is stationary mixed autoregressive moving average
models are called Auto Regressive Integrated Moving Average models.
Because it can incorporate independent regressor variables as arguments, linear transfer function (LTF) analysis is a potentially useful methodology from among the various autoregressive moving average
(ARIMA) techniques that are periodically applied to public utility demand analysis.
The autoregressive (AR) model for the local compliances followed by the moving average measurement allows the compliance measurement sequence to be described as an autoregressive moving average
(ARMA) random process (Hayes 1996).
The mean equation is specified as an autoregressive moving average
process, ARMA (p.
1) Unit Root Test (2) Predictive Causality (3) Variance Decompositions (4) The Impulse-Response Functions (5) Integrated Autoregressive Moving Average
The exponential autoregressive moving average
EARMA(p, q) process.