R:带有modeltime :: arima_reg和tidymodels rsample :: fit_resample的错误消息

时间:2020-10-30 04:36:40

标签: r arima tidymodels

我正在尝试将fit_resample()与arima_reg()一起使用,并且收到一条我无法理解的错误消息。

我正在使用以下代码:

library(modeltime)
library(tidymodels)

df<-data.frame(day=seq(as.Date("2020-1-1"), as.Date("2020-3-31"), "days"), value=sample(1:100, length(seq(as.Date("2020-1-1"), as.Date("2020-3-31"), "days"))))

splits<-sliding_window(df, lookback = Inf, skip=6, assess_start = 7, assess_stop = 14, complete = T)

arima_reg() %>% set_engine("auto_arima")%>% fit_resamples(value~day, data=df, resamples=splits)

我收到以下错误消息:

x Slice01:模型:错误:未提供日期或日期时间变量。请提供日期或日期时间变量作为...

x Slice02:模型:错误:未提供日期或日期时间变量。请提供日期或日期时间变量作为...

x Slice03:模型:错误:未提供日期或日期时间变量。请提供日期或日期时间变量作为...

相同的代码适用于其他模型,即适用于

linear_reg() %>% set_engine("lm")%>% fit_resamples(value~day, data=df, resamples=splits)

并且相同的数据无需重采样即可在auto_arima中使用,即:

arima_reg() %>% set_engine("auto_arima")%>% fit(value~day,data=df)

我有什么想念的吗?


R version 3.5.2 (2018-12-20)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Mojave 10.14.6

Matrix products: default
BLAS: /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.5/Resources/lib/libRlapack.dylib

locale:
[1] de_DE.UTF-8/de_DE.UTF-8/de_DE.UTF-8/C/de_DE.UTF-8/de_DE.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] yardstick_0.0.7  workflows_0.2.1  tune_0.1.1       tidyr_1.1.0      tibble_3.0.3     rsample_0.0.8    recipes_0.1.14  
 [8] purrr_0.3.4      parsnip_0.1.4    modeldata_0.1.0  infer_0.5.3      ggplot2_3.3.2    dplyr_1.0.1      dials_0.0.9     
[15] scales_1.1.1     broom_0.7.2      tidymodels_0.1.1 modeltime_0.3.0 

loaded via a namespace (and not attached):
 [1] tseries_0.10-46      splines_3.5.2        foreach_1.4.4        warp_0.1.0           prodlim_2018.04.18  
 [6] RcppParallel_5.0.2   StanHeaders_2.21.0-6 assertthat_0.2.1     TTR_0.23-4           GPfit_1.0-8         
[11] yaml_2.2.1           globals_0.12.4       ipred_0.9-8          pillar_1.4.6         backports_1.1.8     
[16] lattice_0.20-38      glue_1.4.1           quadprog_1.5-5       pROC_1.16.2          digest_0.6.25       
[21] snakecase_0.11.0     hardhat_0.1.4        colorspace_1.4-1     Matrix_1.2-15        plyr_1.8.4          
[26] timeDate_3043.102    pkgconfig_2.0.3      lhs_1.0.1            DiceDesign_1.8-1     listenv_0.7.0       
[31] slider_0.1.5         gower_0.1.2          lava_1.6.5           generics_0.0.2       ellipsis_0.3.1      
[36] janitor_2.0.1        withr_2.2.0          furrr_0.1.0          urca_1.3-0           nnet_7.3-12         
[41] cli_2.0.2            quantmod_0.4-13      survival_2.43-3      magrittr_1.5         crayon_1.3.4        
[46] forecast_8.5         future_1.11.1.1      fansi_0.4.1          nlme_3.1-137         MASS_7.3-51.1       
[51] xts_0.11-2           class_7.3-14         tools_3.5.2          lifecycle_0.2.0      stringr_1.4.0       
[56] munsell_0.5.0        compiler_3.5.2       rlang_0.4.7          grid_3.5.2           iterators_1.0.10    
[61] rstudioapi_0.11      timetk_2.5.0         gtable_0.3.0         codetools_0.2-15     fracdiff_1.4-2      
[66] curl_4.3             R6_2.4.1             zoo_1.8-4            lubridate_1.7.4      stringi_1.4.6       
[71] parallel_3.5.2       Rcpp_1.0.5           vctrs_0.3.2          rpart_4.1-13         tidyselect_1.1.0    
[76] lmtest_0.9-36 ```    

0 个答案:

没有答案