Autocorrelations Diagnostics

Description

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

Usage

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    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).

See Also

informationTests, Portmanteau

Examples

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    data("eg1.DSE.data.diff", package="dse")
    model <- estVARXls(eg1.DSE.data.diff)
    checkResiduals(model)

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