autoplot.regime_forecast: regime_forecast object ggplot for the outputs on the function...

In adrincont/BMTAR: Bayesian Approach for MTAR Models with Missing Data

Description

Produces a ggplot object for the results of the mtarforecast function.

Usage

## S3 method for class 'regime_forecast'
autoplot(object, type = 1,...)

Arguments

object	Object of class “regim_forecast”. Not NULL
type	numeric giving the type of plot to be computed. Allowed values are 1 for list of “Output, Threshold and Covariate process forecast chains”(the default) or 2 for a list "Output,Threshold and Covariate process" with the estimated forecast and its credibilit bands.
...	other arguments passed to specific methods

Details

Graph the strings for the outputs corresponding to the functions “mtarforecast” which return an object of class “regim_forecast”. The chains corresponding to the samplings in each case do not contain the burning period.

Value

Return a ggplot object.

Author(s)

Valeria Bejarano [e-mail] & Andrey Rincon [e-mail]

References

Calderon, S. and Nieto, F. (2017) Bayesian analysis of multivariate threshold autoregress models with missing data. Communications in Statistics - Theory and Methods 46 (1):296–318. doi:10.1080/03610926.2014.990758.

See Also

mtarforecast

Examples

library(ggplot2)
data('datasim')
estim = mtarns(mtarinipars(tsregime(datasim$Sim$Yt,datasim$Sim$Zt),
list_model = list(pars = list(l = datasim$Sim$l,r = datasim$Sim$r,
orders = list(pj = datasim$pj)))))
forecast = mtarforecast(estim,h = 10)
autoplot.regime_forecast(forecast,1)

adrincont/BMTAR documentation built on Jan. 22, 2022, 2:09 p.m.