intervals.gls
Confidence Intervals on gls Parameters
Description
Approximate confidence intervals for the parameters in the linear model represented by object
are obtained, using a normal approximation to the distribution of the (restricted) maximum likelihood estimators (the estimators are assumed to have a normal distribution centered at the true parameter values and with covariance matrix equal to the negative inverse Hessian matrix of the (restricted) log-likelihood evaluated at the estimated parameters). Confidence intervals are obtained in an unconstrained scale first, using the normal approximation, and, if necessary, transformed to the constrained scale.
Usage
## S3 method for class 'gls' intervals(object, level, which, ...)
Arguments
object | an object inheriting from class |
level | an optional numeric value for the interval confidence level. Defaults to 0.95. |
which | an optional character string specifying the subset of parameters for which to construct the confidence intervals. Possible values are |
... | some methods for this generic require additional arguments. None are used in this method. |
Value
a list with components given by data frames with rows corresponding to parameters and columns lower
, est.
, and upper
representing respectively lower confidence limits, the estimated values, and upper confidence limits for the parameters. Possible components are:
coef | linear model coefficients, only present when |
corStruct | correlation parameters, only present when |
varFunc | variance function parameters, only present when |
sigma | residual standard error. |
Author(s)
José Pinheiro and Douglas Bates [email protected]
References
Pinheiro, J.C., and Bates, D.M. (2000) "Mixed-Effects Models in S and S-PLUS", Springer.
See Also
gls
, intervals
, print.intervals.gls
Examples
fm1 <- gls(follicles ~ sin(2*pi*Time) + cos(2*pi*Time), Ovary, correlation = corAR1(form = ~ 1 | Mare)) intervals(fm1)
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Licensed under the GNU General Public License.