Question

将自定义函数映射到嵌套的daframe

我正在尝试将自定义函数映射到嵌套daframe。此函数使用dplyr和管道“％>％”运算符。

我尝试枚举该函数内部使用的变量，但是它一直无法正常工作。不确定如何执行此操作。


table <- expand.grid(x = c("bird", "dogs"), year = c(2018,2019), week= c(1:52)) %>% 
  mutate(christmas = case_when(week == 52 ~1, TRUE ~ 0),
         ev = case_when(week == 30 ~ 1, TRUE ~ 0),
         alpha = rnorm(n = 208, mean = 10))

 myfun_model_alpha <- function(time_s, param, yr, wk){

        event <- time_s %>% select(christmas,ev )
        time_s <- ts(time_s$alpha, start = c(min(time_s$year),min(time_s$week[time_s$year == min(time_s$year)])),end =  c(max(time_s$year),max(time_s$week[time_s$year == max(time_s$year)])), frequency = 52)
        #time_s <- ts(time_s$alpha, start = c(2017,01),end =  c(2019,20), frequency = 52)
        ts_vec <- window(time_s, end = c(yr, wk))
        leng <- length(ts_vec)
        lambda <- BoxCox.lambda(ts_vec)
        model <-  auto.arima(ts_vec, lambda = lambda, 
                             biasadj = TRUE,
                             xreg =  matrix(c(fourier(ts_vec, K=param), 
                                              event$christmas[1:leng],
                                              event$ev[1:leng]), 
                                            nrow = leng, 
                                            ncol = param*2+2), 
                              seasonal = FALSE)

         forecast <-  forecast(model,
                               16,
                               xreg=matrix(c(fourier(ts_vec, K=param, h=16),
                                          event$christmas[(leng+1):(leng+16)], 
                                          event$ev[(leng+1):(leng+16)]),
                                          nrow = 16, 
                                          ncol = param*2+2))$mean

          pred = tibble(forecast = forecast, 
                        time_index = 1:16,
                        actual = window(time_s, start= c(yr,wk))[2:17])


    return(pred)
  }


# Applying the function t the nested df
table %>% 
  group_by(x) %>% 
  nest() %>% 
  mutate(data = map(data, ~arrange(.x, year, week)),
         model = map(data, ~myfun_model_alpha(.,2,2019, 12))) %>% 
  unnest(model)

它返回错误，例如：“（函数（x）中的错误：未找到对象'圣诞节'”）我正在尝试使用实际值（如果有）来预测16周的水平

在嵌套数据框上使用dplyr内部地图功能

0 个答案: