How to set limits on STLF forecast in R I'm running a STLF forecast against a daily rain dataset (8103 tuples). The column i'm trying to forecast is composed of 0's (no rain) and 1's (rain).
Here is the coded i'm running:
train <- df_zero %>%
  filter_index(. ~ "2019-12-31")

validation <- df_zero %>%
  filter_index("2019-12-31" ~ .)

stlf_model <- stlf(ts(train$choveuHoje, frequency=365), s.window=365, biasadj=TRUE)
fc_stlf <- forecast(stlf_model, biasadj=TRUE)
plot(fc_stlf)
RMSE(fc_stlf$mean, validation)

The resulting forecast:

biasadj=TRUE did not work.
Two questions:

*

*Is it possible to limit the predicted values to be higher than zero?

*Is using RMSE(fc_stlf$mean, validation) a viable way to evaluate the model?


You're applying a method designed for a continuous distribution to a binary outcome. No amount of adjusting the method will fix that. Use a method designed for a binary outcome instead. e.g., a discrete time Markov chain on the space {0,1}.
