# Diagnostics tests of residuals

### Description

Auxiliary function (i.e. not intended for the average user) called by the `getsm`

, `getsv`

and `isat`

functions. The `diagnostics`

function tests for autocorrelation, ARCH and non-normality in a residual series. The autocorrelation and ARCH tests are conducted as Ljung and Box (1979) tests of autocorrelation in the residuals and squared residuals, respectively, whereas the test for non-normality is that of Jarque and Bera (1980)

### Usage

1 2 | ```
diagnostics(x, s2=1, ar.LjungB=c(1,0.025), arch.LjungB=c(1,0.025),
normality.JarqueB=NULL, verbose=FALSE)
``` |

### Arguments

`x` |
numeric vector, typically the residuals from a regression |

`s2` |
the standard deviation of x |

`ar.LjungB` |
a two element vector or NULL. In the former case, the first element contains the AR-order, the second element the p-value. If NULL, then a test for autocorrelation is not conducted |

`arch.LjungB` |
a two element vector or NULL. In the former case, the first element contains the ARCH-order, the second element the p-value. If NULL, then a test for ARCH is not conducted |

`normality.JarqueB` |
a value between 0 and 1 or NULL. In the former case, a test for non-normality is conducted using a significance level equal to the numeric value. If NULL, then no test for non-normality is conducted |

`verbose` |
unused |

### Value

logical. If TRUE, then the residuals series passes the diagnostics tests

### Author(s)

Genaro Sucarrat, http://www.sucarrat.net/

### References

G. Ljung and G. Box (1979): 'On a Measure of Lack of Fit in Time Series Models'. Biometrika 66, pp. 265-270

C. Jarque and A. Bera (1980): 'Efficient Tests for Normality, Homoscedasticity and Serial Independence'. Economics Letters 6, pp. 255-259

### See Also

`getsm`

, `getsv`

, `isat`

### Examples

1 2 | ```
##check for autocorrelation, ARCH and non-normality:
diagnostics(rnorm(40))
``` |

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