Estimation in an Additive Model When the Components Are Linked Parametrically
نویسنده
چکیده
Motivated by a nonparametric GARCH model we consider nonparametric additive autoregression models in the special case that the additive components are linked parametrically+We show that the parameter can be estimated with parametric rate and give the normal limit+ Our procedure is based on two steps+ In the first step nonparametric smoothers are used for the estimation of each additive component without taking into account the parametric link of the functions+ In a second step the parameter is estimated by using the parametric restriction between the additive components+ Interestingly, our method needs no undersmoothing in the first step+
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