aspHetero: Estimate varying residual variance

In AdaptFitOS: Adaptive Semiparametric Additive Regression with Simultaneous Confidence Bands and Specification Tests

Estimate varying residual variance

Description

Estimates a varying residual variance on basis of an asp object. Resulting object can be plotted with simultaneous confidence bands corrected for heteroscedasticity.

Usage

aspHetero(object, xx, nknots=5, knots=NULL, basis="os", 
		 degree=c(3,2), tol=1e-8, niter=100, niter.var=250)

Arguments

object	an asp object.
xx	the covariate.
nknots	the number of knots. Does not apply when knots are given.
knots	the knots. Does not apply if basis=="os". Otherwise, if NULL nknots equidistant knots are used.
basis	the spline basis: "os" (default), "trunc.poly" or "tps".
degree	the spline degree (and penalty order in case of B-splines). Defaults to c(3,2).
tol	tolerance for the convergence criterion. Default is 1e-8.
niter	a maximum number of iterations for residual variance function estimation, default is 100.
niter.var	a maximum number of iterations for the variance of random effects estimation within the residual variance function estimation routine, default is 250.

Value

An object of class asp with varying variances, with additional element sigmax including information on the spline of the varying variance.

References

Wiesenfarth, M., Krivobokova, T., Klasen, S., Sperlich, S. (2012).
Direct Simultaneous Inference in Additive Models and its Application to Model Undernutrition. Journal of the American Statistical Association, 107(500): 1286-1296.

Examples

attach(mcycle)

y=accel
kn1 <- default.knots(times,20)
# fit model with constant residual variance
  fit= asp2(accel~f(times,basis="os",degree=3,knots=kn1,adap=FALSE),
  								niter = 20, niter.var = 200)


# fit model with varying residual variance
fith=aspHetero(fit,times,tol=1e-8)
op <- par(mfrow = c(1,3))
plot(fit);plot(fith)
#sigma() returns the fitted varying residual variance
plot(sort(times),sigma(fith)[order(times)],type="l")
par(op)

AdaptFitOS documentation built on July 21, 2022, 5:10 p.m.