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我在specials使用 fable 包进行预测时尝试使用，但我不知道如何使用它们的语法，也找不到可以用作指南的示例。

我在下面放了一个简单的示例，尝试使用带有MEAN预测模型的窗口，但它给了我一个错误。

任何帮助深表感谢！

# Load libraries
library(fable)
#> Warning: package 'fable' was built under R version 3.6.3
#> Loading required package: fabletools
#> Warning: package 'fabletools' was built under R version 3.6.3
library(tsibble)
#> Warning: package 'tsibble' was built under R version 3.6.3
library(tsibbledata)
#> Warning: package 'tsibbledata' was built under R version 3.6.3
library(lubridate)
#> Warning: package 'lubridate' was built under R version 3.6.3
#> 
#> Attaching package: 'lubridate'
#> The following object is masked from 'package:tsibble':
#> 
#>     interval
#> The following objects are masked from 'package:base':
#> 
#>     date, intersect, setdiff, union
library(dplyr)
#> Warning: package 'dplyr' was built under R version 3.6.3
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:lubridate':
#> 
#>     intersect, setdiff, union
#> The following object is masked from 'package:tsibble':
#> 
#>     id
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

# Run example
aus_retail %>%
  filter(
    State %in% c("New South Wales", "Victoria"),
    Industry == "Department stores"
  ) %>% 
  model(
    snaive = SNAIVE(Turnover),
    mean_f = MEAN(Turnover, window(size = 12))
  )
#> Error in hasTsp(x): argument "x" is missing, with no default

由reprex 包（v0.3.0）于 2020 年 4 月 23 日创建

sessionInfo()
#> R version 3.6.2 (2019-12-12)
#> Platform: x86_64-w64-mingw32/x64 (64-bit)
#> Running under: Windows Server x64 (build 17763)
#> 
#> Matrix products: default
#> 
#> locale:
#> [1] LC_COLLATE=English_Ireland.1252  LC_CTYPE=English_Ireland.1252   
#> [3] LC_MONETARY=English_Ireland.1252 LC_NUMERIC=C                    
#> [5] LC_TIME=English_Ireland.1252    
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#> [1] dplyr_0.8.5       lubridate_1.7.8   tsibbledata_0.1.0 tsibble_0.8.6    
#> [5] fable_0.1.2       fabletools_0.1.3 
#> 
#> loaded via a namespace (and not attached):
#>  [1] Rcpp_1.0.3       compiler_3.6.2   pillar_1.4.3     highr_0.8       
#>  [5] tools_3.6.2      digest_0.6.23    evaluate_0.14    lifecycle_0.2.0 
#>  [9] tibble_3.0.1     gtable_0.3.0     anytime_0.3.7    pkgconfig_2.0.3 
#> [13] rlang_0.4.5      yaml_2.2.0       xfun_0.12        stringr_1.4.0   
#> [17] knitr_1.27       generics_0.0.2   vctrs_0.2.4      grid_3.6.2      
#> [21] tidyselect_1.0.0 glue_1.4.0       R6_2.4.1         rmarkdown_2.1   
#> [25] purrr_0.3.4      ggplot2_3.3.0    tidyr_1.0.2      magrittr_1.5    
#> [29] scales_1.1.0     ellipsis_0.3.0   htmltools_0.4.0  assertthat_0.2.1
#> [33] colorspace_1.4-1 stringi_1.4.5    munsell_0.5.0    crayon_1.3.4
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1 回答 1

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fable 包使用公式样式接口进行模型规范，它与功能非常相似lm()。特价商品包含在模型公式的右侧，如果支持多个特价商品，它们可以相加包含。而不是MEAN(Turnover, window(size = 12))，应该是MEAN(Turnover ~ window(size = 12)。对于ARIMA()可以有很多特价商品的模型，您可以使用ARIMA(Turnover ~ pdq(0,1,4) + PDQ(3,1,0)).

# Load libraries
library(fable)
library(tsibble)
library(tsibbledata)
library(lubridate)
library(dplyr)

# Run example
aus_retail %>%
  filter(
    State %in% c("New South Wales", "Victoria"),
    Industry == "Department stores"
  ) %>% 
  model(
    snaive = SNAIVE(Turnover),
    mean_f = MEAN(Turnover ~ window(size = 12))
  )
#> # A mable: 2 x 4
#> # Key:     State, Industry [2]
#>   State           Industry          snaive   mean_f 
#>   <chr>           <chr>             <model>  <model>
#> 1 New South Wales Department stores <SNAIVE> <MEAN> 
#> 2 Victoria        Department stores <SNAIVE> <MEAN>

由reprex 包（v0.3.0）于 2020-05-08 创建

于 2020-05-08T07:38:44.537 回答