pred.robustgam: Prediction method for robustgam

In robustgam: Robust Estimation for Generalized Additive Models

Description

A prediction function for output of robustgam.

Usage

pred.robustgam(fit, data, type="response")

Arguments

fit	fit object of robustgam
data	a data.frame object. Call the variable X if there is only one covariate. Otherwise, call the first variable X1, the second one X2, and so on.
type	type of output

Value

predict.comp	a matrix containing the individual additive components for each covariates.
predict.values	the type of output required by type. For example, if type="response", the predicted values of the data is outputed.

Author(s)

Raymond K. W. Wong <[e-mail]>

References

Raymond K. W. Wong, Fang Yao and Thomas C. M. Lee (2013) Robust Estimation for Generalized Additive Models. Journal of Graphical and Computational Statistics, to appear.

See Also

robustgam

Examples

# load library
library(robustgam)

# test function
test.fun <- function(x, ...) {
  return(2*sin(2*pi*(1-x)^2))
}

# some setting
set.seed(1234)
true.family <- poisson()
out.prop <- 0.05
n <- 100

# generating dataset for poisson case
x <- runif(n)
x <- x[order(x)]
true.eta <- test.fun(x)
true.mu <- true.family$linkinv(test.fun(x))
y <- rpois(n, true.mu) # for poisson case

# create outlier for poisson case
out.n <- trunc(n*out.prop)
out.list <- sample(1:n, out.n, replace=FALSE)
y[out.list] <- round(y[out.list]*runif(out.n,min=3,max=5)^(sample(c(-1,1),out.n,TRUE)))

# robust GAM fit
robustfit <- robustgam(x, y, family=true.family, p=3, c=1.6, sp=0.000143514, show.msg=FALSE,
  smooth.basis='tp')

# ordinary GAM fit
nonrobustfit <- gam(y~s(x, bs="tp", m=3),family=true.family) # m = p for 'tp'

# prediction
x.new <- seq(range(x)[1], range(x)[2], len=1000)
robustfit.new <- pred.robustgam(robustfit, data.frame(X=x.new))$predict.values
nonrobustfit.new <- as.vector(predict.gam(nonrobustfit,data.frame(x=x.new),type="response"))

# plot
plot(x, y)
lines(x.new, true.family$linkinv(test.fun(x.new)), col="blue")
lines(x.new, robustfit.new, col="red")
lines(x.new, nonrobustfit.new, col="green")
legend(0.6, 23, c("true mu", "robust fit", "nonrobust fit"), col=c("blue","red","green"),
  lty=c(1,1,1))

robustgam documentation built on May 2, 2019, 3:23 a.m.