Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library: gam

backfit the estimates for the components of an additive (partial linear) model are calculated. If the local linear smoother is applied, the first derivatives are calculated as well, additionally the second derivatives if the local quadratic smoother is chosen.
fastint fastint estimates the additive components and their derivatives of an additive model using a modification of the integration estimator plus a one step backfit, see Kim, Linton and Hengartner (1997) and Linton (1996)
gamfit gamfit provides an interactive tool for fitting additive models
gammain sets defaults for library gam
gamopt gamopt defines a list with optional parameters in gam macros. The list is either created or new options are appended to an existing list. Note that gamopt does accept _any_ values for the parameters without validity.
gamout creates a nice output for GAM. ! auxiliary macro !
gamtest tests all abovementioned macros of gam.lib
gintest estimation of the univariate additive functions in a separable generalized additive model using Nad.Watson, local linear or local quadratic
gintestpl gintestpl fits an additive generalized partially linear model E[y|x,t] = G(x*b + m(t)). This macro offers a convenient interface for GPLM estimation. A preparation of data is performed (inclusive sorting).
interact interact estimates a model with interaction terms. It is using the marginal integration estimator with a local polynomial smoother. For details see Sperlich, Tjostheim, Yang (1997)
intertest1 intertest1 is testing for interaction of x_1 and x_2 in an additive regression model. It is looking at the interation estimate and using wild bootstrap. For details see Sperlich, Tjostheim, Yang (1997)
intertest2 intertest2 is testing for interaction of x_1 and x_2 in an additive regression model. It is looking at the estimate of the mixed derivative of the joint influence and using wild bootstrap. For details see Sperlich, Tjostheim, Yang (1997)
intest estimation of the univariate additive functions in a separable additive model using Nad.Watson, local linear or local quadratic
intest1 estimation of the univariate additive functions in a separable additive model using Nad.Wat.
intest2d estimation of a bivariate joint influence function and its derivatives in a model with possible interaction. When loc.lin.smoother is chosen you get the function estimate and the first derivatives in the first and second direction, when loc.quadr.smoother is chosen you get the function and the mixed derivative estimate.
intestpl estimation of the univariate additive functions in a separable additive partial linear model using local polynomial estimation
pcad pcad estimates the additive components, the significant directions and the regression on principal components
wavetest Additive component analysis in additive separable models using wavelet estimation. An additive component can be tested against a given polynomial form with degree p, e.g. when p is set to zero we test for significant influence of that component. For details see Haerdle, Sperlich, Spokoiny (1997).

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

(C) MD*TECH Method and Data Technologies, 28.6.1999