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 enter image description here

it is wrong result, but the main is that forecast on 1 year age ahead has static values(like historical mean) enter image description here

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.

  • $\begingroup$ ets() probably selects a non-seasonal and non-trended model, which yields flat line forecasts. Here are a few similar questions and answers (from me). $\endgroup$ Commented Jan 10, 2019 at 13:17
  • $\begingroup$ @StephanKolassa, i will check i and write you. $\endgroup$
    – psysky
    Commented Jan 10, 2019 at 14:08
  • $\begingroup$ @StephanKolassa,can forecast package set seasonal model using ets()? i can see where do it in argument. $\endgroup$
    – psysky
    Commented Jan 10, 2019 at 14:11
  • $\begingroup$ You can force ets() to use an additive seasonal model with the parameter model="ZZA", or a multiplicative one using model="ZZM". Unfortunately, there is no way to specify either one. However, if ets() chooses a non-seasonal model, it will likely have good reasons for it. I would be skeptical about being able to improve on its model selection. Do seasonal models truly improve out-of-sample forecast accuracy? $\endgroup$ Commented Jan 10, 2019 at 15:35
  • $\begingroup$ Incidentally, does your time series structure have the correct frequency attribute? If not, then ets() will not do anything seasonal. Why Does ETS Say My Data Has No Seasonality? $\endgroup$ Commented Jan 10, 2019 at 15:37


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