Additive nonlinear autoregressive model
Additive nonlinear autoregressive model.
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-(j-1)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):20-25 (2001)
Wood and Augustin, GAMs with integrated model selection using penalized regression splines and applications to environmental modelling. Ecological Modelling 157:157-177 (2002)
#fit an AAR model: mod <- aar(log(lynx), m=3) #Summary informations: #summary(mod) #Diagnostic plots: plot(mod)
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