
This function allows the user to obtain draws from the (parametric) bootstrap distribution of the fitted model's parameters.
boot.mle(model, B = 200, seed = NULL, start = NULL,
method = "Nelder-Mead")
mle
object corresponding to the fitted model.
Requested number of bootstrap samples.
A seed may be specified (see set.seed
)
Starting values for the optimization algorithm (if is.null(start)==TRUE
, the fitted model's parameters are used as starting values).
mle
object corresponding to the fitted model.
Requested number of bootstrap samples.
The specified seed (see set.seed
)
Array containing realized values from the bootstrap distribution of the maximum likelihood parameter estimators.
The bootstrap distributions of two goodness-of-fit statistics: Anderson-Darling statistic and Pearson's correlation coefficient for the pair ("observed quantiles","fitted quantiles").
Bootstrap p-values for the two goodness-of-fit statistics.
The proportion of bootstrap samples for which optimization failed using the specified starting values.
The total amount of time required to generate B
bootstrap samples.
Parametric bootstrap -- see References.
Davison, A.C., and Hinkley, D.V. (1997). Bootstrap methods and their application. Cambridge University Press.
# NOT RUN {
data(yarns)
x <- yarns$x
fit.x <- mle(x,'weibull',c(.1,.1))
boot.x <- boot.mle(fit.x,B=10)
boot.x$par.star
boot.x$p.value
# }
Run the code above in your browser using DataLab