# estimation: Parameters estimation of a time series. In weakARMA: Tools for the Analysis of Weak ARMA Models

 estimation R Documentation

## Parameters estimation of a time series.

### Description

Estimates the parameters of a time series for given orders `p` and `q`

### Usage

```estimation(p = NULL, q = NULL, y, meanparam = FALSE)
```

### Arguments

 `p` Order of AR, if `NULL`, MA is computed. `q` Order of MA, if `NULL`, AR is computed. `y` Univariate time series. `meanparam` Logical argument if the mean parameter has to be computed or not. If FALSE μ is not computed.

### Details

This function uses the algorithm BFGS in the function optim to minimize our objective function `meansq`.

### Value

List of estimate coefficients:

`mu`

Mean parameter

.

`ar`

Vector of AR coefficients with length is equal to `p`.

`ma`

Vector of MA coefficients with length is equal to `q`.

`sigma.carre`

Mean square residuals.

### References

Francq, C. and Zakoïan, J. 1998, Estimating linear representations of nonlinear processes Journal of Statistical Planning and Inference, vol. 68, no. 1, pp. 145-165.

### Examples

```y<-sim.ARMA(1000,ar = c(0.9,-0.3), ma = 0.2, method = "product")
estimation(p = 2, q = 1, y = y)

estimation(p = 1, q = 1, y = CAC40return.sq, meanparam = TRUE)

```

weakARMA documentation built on April 5, 2022, 1:16 a.m.