# checkResiduals: Autocorrelations Diagnostics In dse: Dynamic Systems Estimation (Time Series Package)

## Description

Calculate autocorrelation diagnostics of a time series matrix or TSdata or residuals of a TSestModel

## Usage

 ```1 2 3 4 5 6 7 8``` ``` checkResiduals(obj, ...) ## Default S3 method: checkResiduals(obj, ac=TRUE, pac=TRUE, select=seq(nseries(obj)), drop=NULL, plot.=TRUE, graphs.per.page=5, verbose=FALSE, ...) ## S3 method for class 'TSdata' checkResiduals(obj, ...) ## S3 method for class 'TSestModel' checkResiduals(obj, ...) ```

## Arguments

 `obj` An TSestModel or TSdata object. `ac` If TRUE the auto-correlation function is plotted. `pac` If TRUE the partial auto-correlation function is plotted. `select` Is used to indicate a subset of the residual series. By default all residuals are used. `drop` Is used to indicate a subset of the residual time periods to drop. All residuals are used with the default (NULL).Typically this can be used to get rid of bad initial conditions (eg. drop=seq(10) ) or outliers. `plot.` If FALSE then plots are not produced. `graphs.per.page` Integer indicating number of graphs to place on a page. `verbose` If TRUE then the auto-correlations and partial auto-correlations are printed if they are calculated. `...` arguments passed to other methods.

## Details

This is a generic function. The default method works for a time series matrix which is treated as if it were a matrix of residuals. However, in a Box-Jenkins type of analysis the matrix may be data which is being evaluated to determine a model. The method for a TSestModel evaluates the residuals calculated by subtracting the output data from the model predictions.

## Value

A list with residual diagnostic information: residuals, mean, cov, acf= autocorrelations, pacf= partial autocorrelations.

## Side Effects

Diagnostic information is printed and plotted if a device is available. Output graphics can be paused between pages by setting par(ask=TRUE).

`informationTests`, `Portmanteau`
 ```1 2 3``` ``` data("eg1.DSE.data.diff", package="dse") model <- estVARXls(eg1.DSE.data.diff) checkResiduals(model) ```