HI all,
I have a few questions:

Is there a code to extract the optimal smoothing constant once you have run the ETS model?
(the example shows α =0.84 )

Is there a code to extract the ℓ0 once you have run the ETS model?
( ℓ0 for in the year 1959 , (in the example is = 39.54))

How do you get to 39.54? ( I don´t understand how the calculation is done and why)
# Estimate parameters
fit < algeria_economy %>%
*model(ETS(Exports ~ error("A") + trend("N") + season("N")))*
fc < fit %>%
forecast(h = 5)
Thanks in advance!
The fpp3
library doesn't include the algeria_economy
dataset, but aus_airpassengers
is similar
library(fpp3)
fit < aus_airpassengers %>%
model(ETS(Passengers ~ error("A") + trend("N") + season("N")))
fc < fit %>%
forecast(h = 5)
report(fit)
#> Series: Passengers
#> Model: ETS(A,N,N)
#> Smoothing parameters:
#> alpha = 0.9998998
#>
#> Initial states:
#> l[0]
#> 7.319845
#>
#> sigma^2: 6.3296
#>
#> AIC AICc BIC
#> 271.6389 272.1970 277.1894
Chapter 8 gives more detail of calculations in the context of state models.
1 Like
many thanks! report is exactly what I needed
system
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