I have some models built with the
auto.arima function from the
forecast package. I'm modeling a variable called 'natural efluent energy' (ena), which is how much energy you can extract from some Hydrography region. There are 2 regressor variables (rainfall precipitation from period $t$ and $t-1$.)
Each region has it's own model - some series show positive trend, some shows negative trend, and some seems stationary. The problem is that some forecasts 'from
auto.arima' are giving values higher/lower than usual (some forecasts give me negative values, which are not possible).
My original call is below:
m1 = auto.arima(serie, xreg = regvars)
For the data on the link, I changed it to
m1 = auto.arima(serie, xreg = regvars, max.P = 0, max.Q = 0, stationary = TRUE)
Then I get good forecasts in this case. My question is, what these parameters(
max.Q) actually control, and how they relate to the trend show by my model variable?
Here is a link for the historic data: http://www.datafilehost.com/download-7718b3fc.html
And here a link for the forecast regressors: http://www.datafilehost.com/download-ca44dfa4.html
And here a link of mean historic values, the forecast must fall between these values: http://www.datafilehost.com/download-e1e265b7.html
My data starts at 2001/Jun, so the serie is:
y = ts(dframe$ena, freq = 12, start = c(2001, 6))