coef.isat: Extraction functions for 'isat' objects
In gets: General-to-Specific (GETS) Modelling and Indicator Saturation Methods

coef.isat

R Documentation

Extraction functions for 'isat' objects

Description

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(s)

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

Examples

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

gets documentation built on Sept. 11, 2024, 9:03 p.m.