TETS( y, u =NULL, model ="???", s = frequency(y), h =2* s, criterion ="aicc", forIntervals =FALSE, bootstrap =FALSE, nSimul =5000, verbose =FALSE, alphaL = c(0,1), betaL = alphaL, gammaL = alphaL, phiL = c(0.8,0.98), p0 =-99999, Ymin =-Inf, Ymax =Inf)
Arguments
y: a time series to forecast (it may be either a numerical vector or a time series object). This is the only input required. If a vector, the additional input s should be supplied compulsorily (see below).
u: a matrix of input time series. If the output wanted to be forecast, matrix u should contain future values for inputs.
model: the model to estimate. It is a single string indicating the type of model for each component with one or two letters:
Error: ? / A
Trend: ? / N / A / Ad
Seasonal: ? / N / A
s: seasonal period of time series (1 for annual, 4 for quarterly, ...)
h: forecast horizon. If the model includes inputs h is not used, the lenght of u is used instead.
criterion: information criterion for identification ("aic", "bic" or "aicc").