R:自动移动平均线给出错误

时间:2017-10-29 09:10:32

标签: r ggplot2 forecasting

我想将时间序列与其移动平均线一起绘制,如a Forecasting: Principles and Practices中的示例,我使用自己的时间序列salests

     Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2015 110 115  92 120 125 103 132 136 114 139 143 119
2016 150 156 130 169 166 142 170 173 151 180 184 163

然后我使用与书中类似的代码:

autoplot(salests, series="Sales") +
  forecast::autolayer(ma(salests, 5), series="5 Moving Average")

但我收到错误:

Error: Invalid input: date_trans works with objects of class Date only

我做错了什么?我似乎只是在关注这本书。

提前致谢

1 个答案:

答案 0 :(得分:2)

以下是一些可以帮助您的想法。

# I start reading your dataset
df1 <- read.table(text='
     Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
2015 110 115  92 120 125 103 132 136 114 139 143 119
2016 150 156 130 169 166 142 170 173 151 180 184 163
', header=T)

# Set locale to 'English' if you have a different setting
Sys.setlocale( locale='English' )

# I reshape your dataset in long format
library(reshape)
df2 <- melt(df1)
df2$time <- paste0("01-",df2$variable,'-',rep(rownames(df1), ncol(df1)))
df2$time <- as.Date(df2$time, "%d-%b-%Y")
( df2 <- df2[order(df2$time),] )

#        variable value       time
# 1       Jan   110 2015-01-01
# 3       Feb   115 2015-02-01
# 5       Mar    92 2015-03-01
# 7       Apr   120 2015-04-01
# 9       May   125 2015-05-01
# 11      Jun   103 2015-06-01
# 13      Jul   132 2015-07-01
# 15      Aug   136 2015-08-01
# 17      Sep   114 2015-09-01
# 19      Oct   139 2015-10-01
# 21      Nov   143 2015-11-01
# 23      Dec   119 2015-12-01
# 2       Jan   150 2016-01-01
# 4       Feb   156 2016-02-01
# 6       Mar   130 2016-03-01
# 8       Apr   169 2016-04-01
# 10      May   166 2016-05-01
# 12      Jun   142 2016-06-01
# 14      Jul   170 2016-07-01
# 16      Aug   173 2016-08-01
# 18      Sep   151 2016-09-01
# 20      Oct   180 2016-10-01
# 22      Nov   184 2016-11-01
# 24      Dec   163 2016-12-01

现在创建一个时间序列ts对象

( salests <- ts(df2$value, frequency=12, start = c(2015,1)) )
#   Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
# 1 110 115  92 120 125 103 132 136 114 139 143 119
# 2 150 156 130 169 166 142 170 173 151 180 184 163

并绘制它:

library(ggfortify)
library(forecast)
autoplot(salests)  +
  forecast::autolayer(ma(salests, 5), series="5 Moving Average")

enter image description here