Extraction functions for 'isat' objects

Extraction functions for objects of class 'isat'

Usage

# S3 method for class 'isat'
coef(object, ...)
  # S3 method for class 'isat'
fitted(object, ...)
  # S3 method for class 'isat'
logLik(object, ...)
  # S3 method for class 'isat'
plot(x, col=c("red","blue"), lty=c("solid","solid"),
    lwd=c(1,1), coef.path=TRUE, ...)
  # S3 method for class 'isat'
predict(object, n.ahead=12, newmxreg=NULL, newindex=NULL,
    n.sim=2000, probs=NULL, ci.levels=NULL, quantile.type=7,
    return=TRUE, verbose=FALSE, plot=NULL, plot.options=list(), ...)
  # S3 method for class 'isat'
print(x, signif.stars=TRUE, ...)
  # S3 method for class 'isat'
residuals(object, std=FALSE, ...)
  # S3 method for class 'isat'
sigma(object, ...)
  # S3 method for class 'isat'
summary(object, ...)
  # S3 method for class 'isat'
vcov(object, ...)

Arguments

object: an object of class 'isat'
x: an object of class 'isat'
std: logical. If FALSE (default), then the mean residuals are returned. If TRUE, then the standardised residuals are returned
n.ahead: integer that determines how many steps ahead predictions should be generated (the default is 12)
newmxreg: a matrix of n.ahead rows and NCOL(mxreg) columns with the out-of-sample values of the mxreg regressors
newindex: NULL (default) or the date-index for the zoo object returned by predict.arx. If NULL, then the function uses the in-sample index to generate the out-of-sample index
n.sim: integer, the number of replications used for the generation of the forecasts
probs: NULL (default) or a vector with the quantile-levels (values strictly between 0 and 1) of the forecast distribution. If NULL, then no quantiles are returned unless ci.levels is non-NULL
ci.levels: NULL (default) or a vector with the confidence levels (expressed as values strictly between 0 and 1) of the forecast distribution. The upper and lower values of the confidence interval(s) are returned as quantiles
quantile.type: an integer between 1 and 9 that selects which algorithm to be used in computing the quantiles, see the argument type in quantile
return: logical. If TRUE (default), then the out-of-sample predictions are returned. The value FALSE, which does not return the predictions, may be of interest if only a prediction plot is of interest
verbose: logical with default FALSE. If TRUE, then additional information (typically the quantiles and/or the simulated series) used in the generation of forecasts is returned. If FALSE, then only the forecasts are returned
plot: NULL (default) or logical. If NULL, then the value set by options$plot (see options) determines whether a plot is produced or not. If TRUE, then the out-of-sample forecasts are plotted.
plot.options: a list of options related to the plotting of forecasts, see 'Details'
col: colours of fitted (default=red) and actual (default=blue) lines
lty: types of fitted (default=solid) and actual (default=solid) lines
lwd: widths of fitted (default=1) and actual (default=1) lines
coef.path: logical. Only applicable if there are retained indicators after the application of isat
signif.stars: logical. If TRUE, then p-values are additionally encoded visually, see printCoefmat
...: additional arguments

Details

The plot.options argument is a list that controls the prediction plot, see 'Details' in predict.arx

Value

coef:: numeric vector containing parameter estimates
fitted:: a zoo object with fitted values
logLik:: a numeric, the log-likelihood (normal density)
plot:: plot of the fitted values and the residuals
predict:: a vector of class zoo containing the out-of-sample forecasts, or a matrix of class zoo containing the out-of-sample forecasts together with prediction-quantiles, or - if return=FALSE - NULL
print:: a print of the estimation results
residuals:: a zoo object with the residuals
sigma:: the regression standard error ('SE of regression')
summary:: a print of the items in the isat object
vcov:: variance-covariance matrix

Author

Felix Pretis, http://www.felixpretis.org/
James Reade, https://sites.google.com/site/jjamesreade/
Moritz Schwarz, https://www.inet.ox.ac.uk/people/moritz-schwarz/
Genaro Sucarrat, http://www.sucarrat.net/

Examples

##step indicator saturation:
set.seed(123)
y <- rnorm(30)
isatmod <- isat(y)
#> 
#> SIS block 1 of 2:
#> 15 path(s) to search
#> Searching: 
#> 1 
#> 2 
#> 3 
#> 4 
#> 5 
#> 6 
#> 7 
#> 8 
#> 9 
#> 10 
#> 11 
#> 12 
#> 13 
#> 14 
#> 15 
#> 
#> SIS block 2 of 2:
#> 14 path(s) to search
#> Searching: 
#> 1 
#> 2 
#> 3 
#> 4 
#> 5 
#> 6 
#> 7 
#> 8 
#> 9 
#> 10 
#> 11 
#> 12 
#> 13 
#> 14 
#> 
#> GETS of union of retained SIS variables... 
#> 
#> GETS of union of ALL retained variables...

##print results:
print(isatmod)
#> 
#> Date: Sat Jul 27 15:29:50 2024 
#> Dependent var.: y 
#> Method: Ordinary Least Squares (OLS)
#> Variance-Covariance: Ordinary 
#> No. of observations (mean eq.): 30 
#> Sample: 1 to 30 
#> 
#> SPECIFIC mean equation:
#> 
#>             coef std.error t-stat p-value
#> mconst -0.047104  0.179111 -0.263  0.7944
#> 
#> Diagnostics and fit:
#> 
#>                     Chi-sq df p-value  
#> Ljung-Box AR(1)   0.046575  1 0.82913  
#> Ljung-Box ARCH(1) 3.367118  1 0.06651 .
#> ---
#> Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#>                           
#> SE of regression   0.98103
#> R-squared          0.00000
#> Log-lik.(n=30)   -41.49361

##plot the fitted vs. actual values, and the residuals:
plot(isatmod)


##print the entries of object 'isatmod':
summary(isatmod)
#>                     Length Class      Mode     
#> ISfinalmodels        1     -none-     list     
#> ISnames              0     -none-     NULL     
#> time.started         1     -none-     character
#> time.finished        1     -none-     character
#> call                 2     -none-     call     
#> no.of.estimations    1     -none-     numeric  
#> terminals            1     -none-     list     
#> terminals.results    4     -none-     numeric  
#> best.terminal        1     -none-     numeric  
#> specific.spec        1     -none-     numeric  
#> no.of.getsFun.calls  1     -none-     numeric  
#> gets.type            1     -none-     character
#> date                 1     -none-     character
#> version              1     -none-     character
#> aux                 15     -none-     list     
#> n                    1     -none-     numeric  
#> k                    1     -none-     numeric  
#> df                   1     -none-     numeric  
#> coefficients         1     -none-     numeric  
#> mean.fit            30     zoo        numeric  
#> residuals           30     zoo        numeric  
#> rss                  1     -none-     numeric  
#> sigma2               1     -none-     numeric  
#> vcov.mean            1     -none-     numeric  
#> logl                 1     -none-     numeric  
#> var.fit             30     zoo        numeric  
#> std.residuals       30     zoo        numeric  
#> mean.results         4     data.frame list     
#> diagnostics          6     -none-     numeric  

##extract coefficients of the simplified (specific) model:
coef(isatmod)
#>      mconst 
#> -0.04710376 

##extract log-likelihood:
logLik(isatmod)
#> 'log Lik.' -41.49361 (df=1)

##extract the coefficient-covariance matrix of simplified
##(specific) model:
vcov(isatmod)
#>            mconst
#> mconst 0.03208071

##extract and plot the fitted values:
mfit <- fitted(isatmod)
plot(mfit)


##extract and plot (mean) residuals:
epshat <- residuals(isatmod)
plot(epshat)


##extract and plot standardised residuals:
zhat <- residuals(isatmod, std=TRUE)
plot(zhat)


##generate forecasts of the simplified (specific) model:
predict(isatmod, newmxreg=matrix(1,12,1), plot=TRUE)

#>          31          32          33          34          35          36 
#> -0.04710376 -0.04710376 -0.04710376 -0.04710376 -0.04710376 -0.04710376 
#>          37          38          39          40          41          42 
#> -0.04710376 -0.04710376 -0.04710376 -0.04710376 -0.04710376 -0.04710376

Extraction functions for 'isat' objects

Usage

Arguments

Details

Value

Author

See also

Examples