Additive nonlinear autoregressive model.
1  aar(x, m, d=1, steps=d, series)

x 
time series 
m, d, steps 
embedding dimension, time delay, forecasting steps 
series 
time series name (optional) 
Nonparametric additive autoregressive model of the form:
x[t+steps] = mu + sum_j s_j(x[t(j1)d])
where s_j are nonparametric univariate functions of lagged time series values. They are represented by cubic regression splines. s_j are estimated together with their level of smoothing using routines in the mgcv package (see references).
An object of class nlar
, subclass aar
, i.e. a list
with mostly internal structures for the fitted gam
object.
Antonio, Fabio Di Narzo
Wood, mgcv:GAMs and Generalized Ridge Regression for R. R News 1(2):2025 (2001)
Wood and Augustin, GAMs with integrated model selection using penalized regression splines and applications to environmental modelling. Ecological Modelling 157:157177 (2002)
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