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我有一个来自 Seasonal 包的矩阵输出，我过滤掉“预测”列，只留下时间（月份）和“lowerci”和“upperci”条目。这是通过以下方式完成的： season13201101FL.forecast[,c('lowerci','upperci')]

数据样本：

           lowerci  upperci
Oct 2017 2415.8826 3083.332
Nov 2017 2217.2670 3238.572
Dec 2017 1976.0041 3181.648
Jan 2018 2048.9771 3577.373
Feb 2018 2046.3051 3834.099

这是“mts”类。我正在使用 highcharter 库来绘制我的价值观。series.keys但是，即使我用来映射，它似乎也没有同时使用“lowerci”和“upperci”列：

hc <- highchart(type = "stock") %>% 
  hc_add_series(season13201101FL, id = "Original", name = "Original-FL") %>% 
  hc_add_series(season13201101FL.seasonalData, id = "Seasonally Adjusted-FL", name = "Seasonally Adjusted") %>% 
  hc_add_series(season13201101FL.forecast[,c('forecast')], id = "Forecast-FL") %>% 
  hc_add_series(season13201101FL.forecast[,c('lowerci','upperci')], id = "ForecastRange-FL", keys = c('x', 'low', 'high'), type = "arearange")
hc

生成的图表显示了原始的、经季节性调整的和预测系列，但显示的预测范围没有连接点的“线”，每个时间条目只有一个实际数据点。如何让 highcharter 看到这是一个arearange系列？ 问题样本

要重现使用以下作为导入 CSV 作为theCSV：

date    count
2008.0027   45778
2008.0874   50460
2008.1667   62162
2008.2514   55999
2008.3333   51571
2008.418    45044
2008.5  46357
2008.5847   48498
2008.6694   45472
2008.7514   47161
2008.8361   41907
2008.918    39131
2009.0027   33810
2009.0877   34469

然后代码是：

library(shiny)
library(highcharter)
library(dplyr)
library(tidyr)
library(seasonal)

seasonData <- ts(theCSV[,-1], frequency = 12, start = c(2008,1));
seasonData.seas <- seas(seasonData);
seasonData.seasonalData <- final(seasonData.seas);
seasonData.forecast <- series(seasonData.seas, "forecast.forecasts");
seasonData.seasComp <- series(seasonData.seas, "seats.seasonal");

    hc <- highchart(type = "stock") %>% 
      hc_add_series(seasonData, id = "Original", name = "Original-FL") %>% 
      hc_add_series(seasonData.seasonalData, id = "Seasonally Adjusted-FL", name = "Seasonally Adjusted") %>% 
      hc_add_series(seasonData.forecast[,c('forecast')], id = "Forecast-FL") %>% 
      hc_add_series(seasonData.forecast[,c('lowerci','upperci')], id = "ForecastRange-FL", keys = c('x', 'low', 'high'), type = "arearange")
    hc;
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1 回答 1

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一种方法是将预测转换为具有值和日期/时间值的数据框。

要获取datetime您可以使用time和as.Date运行的值。然后用于hc_add_series添加数据。

library(highcharter)
library(dplyr)
library(tidyr)
library(seasonal)

seasonData <- AirPassengers
seasonData.seas <- seas(seasonData);
seasonData.seasonalData <- final(seasonData.seas);
seasonData.forecast <- series(seasonData.seas, "forecast.forecasts");
seasonData.seasComp <- series(seasonData.seas, "seats.seasonal");


time <- seasonData.forecast %>%
  stats::time() %>%
  zoo::as.Date() %>% 
  datetime_to_timestamp()

dfforecast <- seasonData.forecast %>% 
  as.data.frame() %>% 
  mutate(time = time)

highchart(type = "stock") %>% 
  hc_add_series(seasonData, id = "Original", name = "Original-FL") %>% 
  hc_add_series(seasonData.seasonalData, id = "Seasonally Adjusted-FL", name     = "Seasonally Adjusted") %>% 
  hc_add_series(seasonData.forecast[,c('forecast')], id = "Forecast-FL") %>% 
  hc_add_series(dfforecast, hcaes(x = time, low = lowerci, high = upperci),     id = "ForecastRange-FL", type = "arearange")

hc

在此处输入图像描述

于 2017-10-23T13:52:27.197 回答