Holt预测R中的多个时间序列

如何解决Holt预测R中的多个时间序列

我正在尝试对多个时间序列进行Holt预测，并将其与我的原始data.frame相结合。考虑以下data.frame，其中有两个人口群体：

library("forecast")

d <- data.frame(SEX       = c("MALE","MALE","FEMALE","FEMALE"),EDUCATION = c("01","01","01"),TIME      = c("2000","2001","2002","2000","2002"),VALUE     = c(120,150,140,90,75,60))

然后我要对两个时间序列进行Holt预测：

male   <- ts(as.numeric(d[1:3,]$VALUE),start=c(2000))
female <- ts(as.numeric(d[4:6,start=c(2000))

forecastmale   <- holt(male,h = 3,damped = FALSE)
forecastfemale <- holt(female,damped = FALSE)

然后我保存结果并与原始数据结合在一起。

forecastmale   <- data.frame(forecastmale[["mean"]])
forecastfemale <- data.frame(forecastfemale[["mean"]])

forecastmale$SEX            <- c("MALE","MALE")
forecastmale$EDUCATION      <- c("01","01")
forecastmale$TIME           <- c("2003","2004","2005")
colnames(forecastmale)[1]   <- "VALUE" 
forecastmale                <- forecastmale[,c(2,3,4,1)]

forecastfemale$SEX          <- c("FEMALE","FEMALE")
forecastfemale$EDUCATION    <- c("01","01")
forecastfemale$TIME         <- c("2003","2005")
colnames(forecastfemale)[1] <- "VALUE"
forecastfemale              <- forecastfemale[,1)]

d <- rbind(d,forecastmale,forecastfemale)

当我只有两个时间序列时，此方法有效。但是，如果我必须预测100个时间序列，那么这并不是一种非常有效的方法。任何人都可以帮助提高编码效率，因此，例如，如果我在data.frame中包括一个额外的填充组，那么我在代码中没有任何更改吗？

解决方法

这是fable包旨在处理的内容。这是一个使用与您相同的数据结构的示例。

library(dplyr)
library(tsibble)
library(fable)

# Artifical data
df <- expand.grid(
    education = 1:3,sex = c("male","female"),year = 1990:2002
  ) %>%
  as_tsibble(index=year,key=c(sex,education)) %>%
  mutate(value = rnorm(78))

# Fit Holt's method to each series and forecast 3 years ahead
df %>%
  model(holt = ETS(value ~ trend("A"))) %>%
  forecast(h=3)
#> # A fable: 18 x 6 [1Y]
#> # Key:     sex,education,.model [6]
#>    sex    education .model  year         value  .mean
#>    <fct>      <int> <chr>  <dbl>        <dist>  <dbl>
#>  1 male           1 holt    2003  N(0.14,1.7)  0.137
#>  2 male           1 holt    2004  N(0.17,1.7)  0.171
#>  3 male           1 holt    2005  N(0.21,1.7)  0.205
#>  4 male           2 holt    2003 N(-0.75,1.5) -0.749
#>  5 male           2 holt    2004 N(-0.84,1.8) -0.837
#>  6 male           2 holt    2005   N(-0.93,2) -0.926
#>  7 male           3 holt    2003  N(0.51,0.7)  0.514
#>  8 male           3 holt    2004  N(0.53,0.7)  0.530
#>  9 male           3 holt    2005  N(0.55,0.7)  0.546
#> 10 female         1 holt    2003 N(0.44,0.98)  0.445
#> 11 female         1 holt    2004 N(0.47,0.98)  0.470
#> 12 female         1 holt    2005  N(0.5,0.98)  0.495
#> 13 female         2 holt    2003 N(0.13,0.89)  0.127
#> 14 female         2 holt    2004 N(0.15,0.89)  0.148
#> 15 female         2 holt    2005 N(0.17,0.89)  0.168
#> 16 female         3 holt    2003  N(0.78,1.8)  0.781
#> 17 female         3 holt    2004  N(0.88,1.8)  0.880
#> 18 female         3 holt    2005  N(0.98,1.8)  0.978

^{由reprex package（v0.3.0）于2020-09-05创建}