Computes a confidence interval for one or more parameters in a
unvariateML object.
Usage
# S3 method for class 'univariateML'
confint(object, parm = NULL, level = 0.95, Nreps = 1000, ...)Arguments
- object
An object of class
univariateML.- parm
Vector of strings; the parameters to calculate a confidence interval for. Each parameter must be a member of
names(object).- level
The confidence level.
- Nreps
Number of bootstrap iterations. Passed to
bootstrapml().- ...
Additional arguments passed to
bootstrapml().
Value
A matrix or vector with columns giving lower and upper confidence
limits for each parameter in parm.
Details
confint.univariateML is a wrapper for bootstrapml() that
computes confidence intervals for the main parameters of object.
The main parameters of object are the members of
names(object). For instance, the main parameters of an object
obtained from mlnorm are mean and sd. The
confidence intervals are parametric bootstrap percentile intervals
with limits (1-level)/2 and 1 - (1-level).
See also
stats::confint() for the generic function and
bootstrapml() for the function used to calculate the
confidence intervals.
Examples
object <- mlinvgauss(airquality$Wind)
confint(object) # 95% confidence interval for mean and shape
#> 2.5% 97.5%
#> mean 9.282952 10.63857
#> shape 44.413492 71.16450
confint(object, "mean") # 95% confidence interval for the mean parameter
#> 2.5% 97.5%
#> 9.293843 10.585785
# confint(object, "variance") # Fails since 'variance isn't a main parameter.