summary.arima.rob: Summary Method for arima.rob Objects

In robustarima: Robust ARIMA Modeling

Description

Returns a summary list for an "arima.rob" object.

Usage

## S3 method for class 'arima.rob'
summary(object, correlation = FALSE, ...)

Arguments

object	an object of class "arima.rob".
correlation	a logical flag: if TRUE, correlation matrices of regression coefficients and ARIMA coefficients are also produced. The default is FALSE.
...	extra arguments passed to or from other methods. The summary method here ignore these arguments.

Details

This function is a method for the generic function summary for class "arima.rob". It can be invoked by calling summary for an object of the appropriate class, or directly by calling summary.arima.rob regardless of the class of the object.

Value

an object of class "summary.arima.rob" which must contain the following components:

ARIMA.model	the same list as the model component of object. See arima.rob.object for details.
reg.coef	a matrix with four columns, containing the regression coefficients, their standard errors, the t-statistics and the corresponding p-values.
regcoef.cov	the estimated covariance matrix for the regression coefficients.
regcoef.corr	the estimated correlation matrix for the regression coefficients. This is only present if corr=T.
AR.coef	a matrix with four columns, containing the AR coefficients, their standard errors, the t-statistics and the p-values.
MA.coef	a matrix with four columns, containing the MA coefficients, their standard errors, the t-statistics and the p-values.
sMA.coef	an array which contains the seasonal moving average parameter, its standard error, the t-statistic and the p-value.
ARIMA.cov	the estimated covariance matrix of the ARMA coefficients.
ARIMA.corr	the estimated correlation matrix of the ARMA coefficients. This is only present if corr=T.
n	the length of the time series.
df	the number of degrees of freedom for the model.
sigma	the estimate of the innovations scale.
call	the image of the original call to arima.rob.
outliers	an object of class "summary.outliers".

See Also

arima.rob, arima.rob.object, summary.

Examples

frip.rr <- arima.rob(log(frip.dat) ~ 1, p=2, d=1)
summary(frip.rr)

Example output

Call:
arima.rob(formula = log(frip.dat) ~ 1, p = 2, d = 1)

Regression model:
 log(frip.dat) ~ 1

ARIMA model:
Ordinary differences: 1 ; AR order: 2 ; MA order: 0 

Regression Coefficients:
            Value  Std. Error t value Pr(>|t|)
(Intercept) 0.0024 0.0005     4.6558  0.0000  

AR Coefficients:
      Value   Std. Error t value Pr(>|t|)
AR(1) -0.3099  0.0537    -5.7742  0.0000 
AR(2) -0.0929  0.0537    -1.7310  0.0843 

Degrees of freedom: 360 total; 356 residual

Innovations standard deviation: 0.01311 

 Number of outliers detected:  9 

Outliers detected:

  Time       Type Impact     t-value 
1 "Mar 1963" "AO" "-0.14567" "13.765"
2 "May 1968" "AO" "-0.39778" "38.099"
3 "Jun 1968" "AO" "-0.15409" "14.551"
4 "Sep 1968" "AO" "-0.04516" " 4.410"
5 "Apr 1969" "LS" " 0.04511" " 3.814"
6 "Sep 1974" "LS" "-0.04351" " 3.767"
7 "Nov 1974" "LS" "-0.04844" " 4.092"
8 "Sep 1976" "AO" " 0.03820" " 3.829"
9 "Apr 1986" "AO" " 0.03935" " 3.932"
attr(,"class")
[1] "char.matrix"

Innovation scale estimate before correcting outliers:
  0.01311 

Innovation scale estimate after correcting outliers:
  0.01215 

robustarima documentation built on May 1, 2021, 1:06 a.m.