confint.QRS {ADVICE} | R Documentation |
Confidence Interval Function
Description
Computes confidence intervals for one or more parameters in a fitted model. There is a default and a method for objects inheriting from class "qrs".
Usage
## S3 method for class 'QRS'
confint(object, parm, level, ...)
Arguments
object |
a fitted model object from the QRS class. |
parm |
a specification of which parameters are to be given confidence intervals, either a vector of numbers or a vector of names. If missing, all parameters are considered. |
level |
a numeric value specifying the required confidence level. |
... |
additional argument(s) for the methods. |
Details
This function computes t-based confidence intervals using n-p degrees of freedom, where n is the number of observations and p is the number of regression coefficients in the full model.
Value
A 2-column matrix giving lower and upper confidence limits (corresponding to the given level) for each parameter. These will be labelled as (1-level)/2 and 1 - (1-level)/2 in
Author(s)
Ladan Tazik, W.J. Braun
See Also
ices.R
Examples
myRegressionData <- rmultreg(100, k=20, p=.1, sdnoise = 1)
pairs(myRegressionData$data)
out <- ices(y ~ ., data = myRegressionData$data) # fit model to simulated data
confint(out) # calculate 95% confidence intervals for all coefficients
myRegressionData$coefficients # compare with true coefficients