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

Quantlet: 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     = 150

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)

bild  = createdisplay(1,2)

dat11 = x[,1]~g1

dat12 = xg[,1]~gest[,1]

dat21 = x[,2]~g2

dat22 = xg[,2]~gest[,2]

setmaskp(dat12,4,4,8)

setmaskp(dat22,4,4,8)

setmaskl(dat12,(1:rows(dat12))',4,1,1)

setmaskl(dat22,(1:rows(dat22))',4,1,1)

show(bild,1,1,dat11,dat12)

show(bild,1,2,dat21,dat22)

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, 21.9.2000