confint.kspm: Confidence interavls for linear part of model parameters
In KSPM: Kernel Semi-Parametric Models

Description Usage Arguments Details Value Author(s) See Also Examples

Computes confidence intervals for one or more parameters in the linear part of a fitted model of class "kspm".

1 2	## S3 method for class 'kspm' confint(object, parm = NULL, level = 0.95, ...)

`object`	an object of class "kspm", usually, a result of a call to `kspm`.
`parm`	a vector of names specifying which parameters are to be given confidence intervals. If missing, all parameters are considered.
`level`	the confidence level required. By default 0.95.
`...`	additional optional argument (currently unused).

For objects of class "kspm", the confidence interval is based on student distribution and effective degree of freedom of the model.

A matrix with column giving lower and upper confidence limits for each parameter. These are labelled as (1-level) / 2 and 1-(1-level)/2 in percentage.

Catherine Schramm, Aurelie Labbe, Celia Greenwood

kspm for fitting model, summary.kspm.

x <- 1:15
z1 <- runif(15, 1, 6)
z2 <- rnorm(15, 1, 2)
y <- 3*x + (z1 + z2)^2 + rnorm(15, 0, 2)
fit <- kspm(y, linear = ~ x, kernel = ~ Kernel(~ z1 + z2,
kernel.function = "polynomial", d= 2, rho = 1, gamma = 0))
confint(fit)