# ARMA_MEAN - ARMA fitted values of conditional mean

Returns an array of cells for the fitted values of the conditional mean.

## Syntax

ARMA_MEAN(X, Order, mean, sigma, phi, theta)

X
is the univariate time series data (a one-dimensional array of cells (e.g., rows or columns)).
Order
is the time order in the data series (i.e., the first data point's corresponding date (earliest date = 1 (default), latest date = 0)).
Value Order
1 Ascending (the first data point corresponds to the earliest date) (default).
0 Descending (the first data point corresponds to the latest date).
Mean
is the ARMA model mean (i.e., mu).
sigma
is the standard deviation of the model's residuals/innovations.
phi
are the parameters of the AR(p) component model (starting with the lowest lag).
theta
are the parameters of the MA(q) component model (starting with the lowest lag).

Warning

ARMA_MEAN() function is deprecated as of version 1.63: use ARMA_FIT function instead.

## Remarks

1. The underlying model is described here.
2. The time series is homogeneous or equally spaced.
3. The time series may include missing values (e.g., #N/A) at either end.
4. The ARMA model fitted values are defined as: $$\hat x_t = \mu + \sum_{i=1}^p \phi_i x_{t-i} + \sum_{j=1}^q \theta_j a_{t-j}$$ Where:
• $\hat x_t$ is the fitted model value (i.e. conditional mean) at time $t$. $$1\leq t \leq T$$
• $T$ is the number of non-missing values in the data sample.
5. The number of parameters in the input argument - phi - determines the order of the AR component.
6. The number of parameters in the input argument - theta - determines the order of the MA component.