coef.isat: Extraction functions for 'isat' objects

Description Usage Arguments Details Value Author(s) See Also Examples

Description

Extraction functions for objects of class 'isat'

Usage

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  ## S3 method for class 'isat'
coef(object, ...)
  ## S3 method for class 'isat'
fitted(object, spec=NULL, ...)
  ## 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,
    return=TRUE, plot=NULL, plot.options=list(), ...)
  ## S3 method for class 'isat'
print(x, ...)
  ## 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'

spec

'mean' or 'variance'

std

logical. If FALSE (default), then the mean residuals are returned. If TRUE, then the standardised residuals are returned

n.ahead

generate forecasts up to n steps ahead (the default is 12)

newmxreg

a matrix (n.ahead rows and NCOL(mxregs) columns) with the out-of-sample values of the mxreg regressors

newindex

date-index for the zoo object returned by predict.arx

return

logical. If TRUE (default), then the out-of-sample forecasts are returned

plot

NULL or logical. If TRUE, then the out-of-sample forecasts are plotted. If NULL (default), then the value set by options determines whether a plot is produced or not.

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

...

additional arguments

Details

The plot.options argument is a list that can contain any of the following arguments:

keep: integer greater than zero (default is 10) that controls the number of in-sample actual values to plot
fitted: If TRUE, then the fitted values as well as actual values are plotted in-sample. The default is FALSE
errors.only: logical or NULL (the default). If TRUE, then only mean forecasts are plotted when spec is set to "both"
legend.loc: character string (the default is "topleft"). Allows the location of the plot legend to be altered
newmactual: numeric vector or NULL (default). Enables the plotting of actual values out-of-sample in addition to the forecasts

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 containing the out-of-sample forecasts

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(s)

Felix Pretis, http://www.felixpretis.org/
James Reade, https://sites.google.com/site/jjamesreade/
Genaro Sucarrat, http://www.sucarrat.net/

See Also

paths, terminals, coef.gets, getsm, arx

Examples

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##step indicator saturation:
set.seed(123)
y <- rnorm(30)
isatmod <- isat(y)

##print results:
print(isatmod)

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

##print the entries of object 'isatmod':
summary(isatmod)

##extract coefficients of the simplified (specific) model:
coef(isatmod)

##extract log-likelihood:
logLik(isatmod)

##extract variance-covariance matrix of simplified
##(specific) model:
vcov(isatmod)

##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 with the simplified
##(specific) model:
predict(isatmod)


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