additive.stage: Stagewise fitting of an additive model

Description Usage Arguments Value Author(s) See Also Examples

Description

Computes the value of an additive model regression estimator at one point using stagewise fitting

Usage

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additive.stage(x, y=NULL, arg=NULL, residu=NULL, deet=NULL, h=1, kernel="gauss",
M=2, vect=FALSE)

Arguments

x

n*d data matrix; the matrix of the values of the explanatory variables

y

n vector or NULL; the values of the response variable; if "residu" is given, then "y" is not used

arg

d-vector; the point where the estimate is evaluated

residu

NULL or n*M matrix of residuals; for each step the n vector of residuals is given; the first residual is the vector of y-observations

deet

NULL or M vector of values 1,...,d; for each step the direction chosen by the optimizer

h

a positive real number; the smoothing parameter of the kernel estimate

kernel

a character; determines the kernel function; either "gauss" or "uniform"

M

integer >=2; the number of iterations

vect

TRUE or FALSE; internal parameter

Value

list of eval, residu, deet, value, and valvec; "eval" is a n*d matrix of the evaluations of the estimated component functions at the data points; "residu" is n*M matrix which contains the sequence of estimates evaluated at the observations; "deet" is M vector of values 1,...,d which indicates for each step the direction chose by the optimization procedure; "value" is a real number giving the estimated value of the regression function at one point; "valvec" is d vector giving the estimated values of the component functions at one point

Author(s)

Jussi Klemela

See Also

pcf.additive,

Examples

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set.seed(1)
n<-100
d<-2 
x<-8*matrix(runif(n*d),n,d)-3
C<-(2*pi)^(-d/2)
phi<-function(x){ return( C*exp(-sum(x^2)/2) ) }
D<-3; c1<-c(0,0); c2<-D*c(1,0); c3<-D*c(1/2,sqrt(3)/2)
func<-function(x){phi(x-c1)+phi(x-c2)+phi(x-c3)}
y<-matrix(0,n,1)
for (i in 1:n) y[i]<-func(x[i,])+0.01*rnorm(1)

as<-additive.stage(x,y) 

arg<-c(0,0)
additive.stage(x,arg=arg,residu=as$residu,deet=as$deet)


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