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Augmented Dickey-Fuller test

`h = adftest(Y)`

`h = adftest(Y,Name,Value)`

```
[h,pValue]
= adftest(___)
```

```
[h,pValue,stat,cValue,reg]
= adftest(___)
```

returns
a logical value with the rejection decision from conducting an augmented
Dickey-Fuller test for a unit root in a univariate time series, `h`

= adftest(`Y`

)`Y`

.

uses
additional options specified by one or more `h`

= adftest(`Y`

,`Name,Value`

)`Name,Value`

pair
arguments.

If any

`Name,Value`

argument is a vector, then all`Name,Value`

arguments specified must be vectors of equal length or length one.`adftest(Y,Name,Value)`

treats each element of a vector input as a separate test, and returns a vector of rejection decisions.If any

`Name,Value`

argument is a row vector, then`adftest(Y,Name,Value)`

returns a row vector.

`adftest`

performs ordinary least squares (OLS) regression to estimate the coefficients in the alternative model.Dickey-Fuller statistics follow nonstandard distributions under the null hypothesis (even asymptotically). Critical values for a range of sample sizes and significance levels have been tabulated using Monte Carlo simulations of the null model with Gaussian innovations, with five million replications per sample size.

For small samples, the tabulated critical values are only valid for Gaussian innovations. For large samples, the tabulated values are still valid for non-Gaussian innovations.

`adftest`

interpolates critical values and p-values from the tables. The tables for test types`'t1'`

and`'t2'`

are identical to those for`pptest`

.

`i10test`

| `kpsstest`

| `lmctest`

| `pptest`

| `vratiotest`