This topic similar with this one R Time Series Analysis forecast result always remains same But I perfrom exponential smoothing model in R.
df=structure(list(date = structure(1:12, .Label = c("01.01.2017",
"01.02.2017", "01.03.2017", "01.04.2017", "01.05.2017", "01.06.2017",
"01.07.2017", "01.08.2017", "01.09.2017", "01.10.2017", "01.11.2017",
"01.12.2017"), class = "factor"), value = c(200L, 100L, 460L,
300L, 280L, 280L, 140L, 180L, 80L, 80L, 180L, 60L), common = structure(c(1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L), .Label = "158150- 01195т", class = "factor")), .Names = c("date",
"value", "common"), class = "data.frame", row.names = c(NA, -12L
))
i perform forecast for each groups separately) using ets function from forecast package (common is grouping variable)
here forecast for initial dataset
it is wrong result, but the main is that forecast on 1 year age ahead has static values(like historical mean)
How can i understand why forecast show same value in exponential smoothing model. Is it possible to fix it?
I can provide my R code, if it is needed.