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
See also: intest pcad

Macro: intest1
Description: estimation of the univariate additive functions in a separable additive model using Nad.Wat.

Usage: gest = intest1(x,y,xg,h,g)
Input:
x n x d matrix , the observed explanatory variable where the directions of interest have to be the first q columns
y n x p matrix , the observed response variables
xg m x q matrix , the grid with m points in each of the q directions of interest
h q x 1 or 1 x 1 matrix , chosen bandwidth for the directions of interest
g d x 1 or 1 x 1 matrix , chosen bandwidth for the directions not of interest
Output:
gest m x q x p matrix, containing the marginal integration estimators

Example:
library("gam")
n     = 250
x     = uniform(n,4)*4-2
g1    = 2*x[,1]
g2    = x[,2]^2 - 4/3
g3    = exp(x[,3])
g4    = sin(1.5*x[,4])
eps   = normal(n,1) * sqrt(0.5)
y     = g1 + g2 + g3 + g4 + eps
xg    = grid(-1.8,0.2,19)
xg    = xg~xg 
h     = #(1.0, 0.75)		; we are interested in
g     = #(1.3, 1.0, 1.5, 1.5)     ; the shape of g1, g2
gest= intest1(x,y,xg,h,g)
Result:
the marginal integration estimator of the additive 
functions, using a multidimensional Nadaraya Watson
see Tjostheim and Auestad, "Nonparametric Identifi-
cation of Nonlinear Time Series: Projections", JASA,
(1994)

Library: gam
See also: intest pcad

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

Author: Korndoerfer & Sperlich 960805
(C) MD*TECH Method and Data Technologies, 28.6.1999