如何使用 R 中的 auto.arima 生成带有日期的未来预测？

Question

i would like to generate forecasts using auto.arima however i dont see future dates populated. How can i get future forecasts with date. I am having weekly data, want to generate forecasts upto Dec 2020

i am using forecast package in R

fit <- auto.arima(zoo_ts)

fcast <- forecast(fit, h=83)

Need weekly forecast from july 2019 with dates having weekly interval. I am not providing any data. Can anyone share how to do it will be great

Answer 1

The forecast package uses ts objects, which are not great for weekly data. The time index is stored numerically in terms of years. So 2019.5385 means week 28 of 2019 (as 28/52 = 0.5385).

An alternative is to use the fable and tsibble packages. Here is an example using weekly data.

library(tsibble)
library(fable)
library(fpp3) # For the data

# Fit the model
fit <- us_gasoline %>% model(arima = ARIMA(Barrels))
# Produce forecasts
fcast <- forecast(fit, h = 83)
fcast
#> # A fable: 83 x 4 [1W]
#> # Key:     .model [1]
#>    .model     Week Barrels .distribution
#>    <chr>    <week>   <dbl> <dist>       
#>  1 arima  2017 W04    8.30 N(8.3, 0.072)
#>  2 arima  2017 W05    8.44 N(8.4, 0.077)
#>  3 arima  2017 W06    8.53 N(8.5, 0.082)
#>  4 arima  2017 W07    8.59 N(8.6, 0.086)
#>  5 arima  2017 W08    8.48 N(8.5, 0.091)
#>  6 arima  2017 W09    8.49 N(8.5, 0.096)
#>  7 arima  2017 W10    8.61 N(8.6, 0.101)
#>  8 arima  2017 W11    8.52 N(8.5, 0.106)
#>  9 arima  2017 W12    8.58 N(8.6, 0.111)
#> 10 arima  2017 W13    8.47 N(8.5, 0.115)
#> # … with 73 more rows

The time index is stored in weeks here. This can be converted to a date using as.Date :

# Convert weekly index to a date
fcast %>% mutate(date = as.Date(Week))
#> # A fable: 83 x 5 [1W]
#> # Key:     .model [1]
#>    .model     Week Barrels .distribution date      
#>    <chr>    <week>   <dbl> <dist>        <date>    
#>  1 arima  2017 W04    8.30 N(8.3, 0.072) 2017-01-23
#>  2 arima  2017 W05    8.44 N(8.4, 0.077) 2017-01-30
#>  3 arima  2017 W06    8.53 N(8.5, 0.082) 2017-02-06
#>  4 arima  2017 W07    8.59 N(8.6, 0.086) 2017-02-13
#>  5 arima  2017 W08    8.48 N(8.5, 0.091) 2017-02-20
#>  6 arima  2017 W09    8.49 N(8.5, 0.096) 2017-02-27
#>  7 arima  2017 W10    8.61 N(8.6, 0.101) 2017-03-06
#>  8 arima  2017 W11    8.52 N(8.5, 0.106) 2017-03-13
#>  9 arima  2017 W12    8.58 N(8.6, 0.111) 2017-03-20
#> 10 arima  2017 W13    8.47 N(8.5, 0.115) 2017-03-27
#> # … with 73 more rows

^{Created on 2019-10-16 by the reprex package (v0.3.0)}