forecast autoplot:: autoplot arguments

[Marcell]

Hi,

I would like to specify some arguments (colour, linetype) of plot in autopilot on a forecast object, but it doesn't work.

Code enclosed

library(forecast)
#> Warning: package 'forecast' was built under R version 3.6.3
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#>   as.zoo.data.frame zoo
library(tidyverse)
#> Warning: package 'tidyverse' was built under R version 3.6.3
#> Warning: package 'ggplot2' was built under R version 3.6.3
#> Warning: package 'tibble' was built under R version 3.6.3
#> Warning: package 'tidyr' was built under R version 3.6.3
#> Warning: package 'dplyr' was built under R version 3.6.3
#> Warning: package 'forcats' was built under R version 3.6.3

ld_y <- c(0, -0.247049511424917, -0.209066160929232, 0.0232083547024029, -0.0573451829158251, 0.0464897709019544, 0.285377182432085, 0.0506005987899635, 0.403417474837009, -0.159173983892748, -0.00178502492425098)
ld_y <- ts(ld_y)

arima <-
  ld_y %>% auto.arima(trace = T,
                      approximation = F,
                      seasonal = F)
#> 
#>  ARIMA(2,0,2) with non-zero mean : Inf
#>  ARIMA(0,0,0) with non-zero mean : -0.2698814
#>  ARIMA(1,0,0) with non-zero mean : 3.614577
#>  ARIMA(0,0,1) with non-zero mean : 3.628257
#>  ARIMA(0,0,0) with zero mean     : -3.277957
#>  ARIMA(1,0,1) with non-zero mean : 8.758265
#> 
#>  Best model: ARIMA(0,0,0) with zero mean

forecast(arima, h = 24) %>% autoplot(
  predict.colour = 'red',
  predict.linetype = 'dashed',
  conf.int = FALSE
)

^{Created on 2020-08-18 by the reprex package (v0.3.0)}

Thank for the help in advance

Marcell

[mitchelloharawild]

The available options for the forecast autoplot() can be found at ?autoplot.forecast.

The colour of the forecasts can be controlled using fcol. Changing the linetype is not supported for the autoplot() method for forecast objects. More flexibility can be achieved if you use the fable package, possibly in combination with the ggdist package to produce custom forecast graphics.

library(forecast)
#> Registered S3 method overwritten by 'quantmod':
#>   method            from
#>   as.zoo.data.frame zoo
library(tidyverse)

ld_y <- c(0, -0.247049511424917, -0.209066160929232, 0.0232083547024029, -0.0573451829158251, 0.0464897709019544, 0.285377182432085, 0.0506005987899635, 0.403417474837009, -0.159173983892748, -0.00178502492425098)
ld_y <- ts(ld_y)

arima <-
  ld_y %>% auto.arima(trace = T,
                      approximation = F,
                      seasonal = F)
#> 
#>  ARIMA(2,0,2) with non-zero mean : Inf
#>  ARIMA(0,0,0) with non-zero mean : -0.2698814
#>  ARIMA(1,0,0) with non-zero mean : 3.614577
#>  ARIMA(0,0,1) with non-zero mean : 3.628257
#>  ARIMA(0,0,0) with zero mean     : -3.277957
#>  ARIMA(1,0,1) with non-zero mean : 8.758265
#> 
#>  Best model: ARIMA(0,0,0) with zero mean

forecast(arima, h = 24) %>% autoplot(fcol = 'red')

^{Created on 2020-08-20 by the reprex package (v0.3.0)}