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dse (version 2014.11-1)

checkResiduals: Autocorrelations Diagnostics

Description

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

Usage

checkResiduals(obj, ...)
    ## S3 method for class 'default':
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.

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).

concept

DSE

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.

See Also

informationTests, Portmanteau

Examples

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

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