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0.1 probit.gam: Generalized Additive Model for Dichotomous Dependent Variables



This function runs a nonparametric Generalized Additive Model (GAM) for dichotomous dependent variables. Syntax> z.out <- zelig(y ~ x1 + s(x2), model = "probit.gam", data = mydata)> x.out <- setx(z.out)> s.out <- sim(z.out, x = x.out) Where s() indicates a variable to be estimated via nonparametric smooth. All variables for which s() is not specified, are estimated via standard parametric methods. Additional Inputs In addition to the standard inputs, zelig() takes the following additional options for GAM models. ˆ method: Controls the fitting method to be used. Fitting methods are selected via a list environment within method=gam.method(). See gam.method() for details. ˆ scale: Generalized Cross Validation (GCV) is used if scale = 0 (see the “Model” section for details) except for Logit models where a Un-Biased Risk Estimator (UBRE) (also see the “Model ” section for details) is used with a scale parameter assumed to be 1. If scale is greater than 1, it is assumed to be the scale parameter/variance and UBRE is used. If scale is negative GCV is used

Year: 2011
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