Description Usage Arguments Details Value Author(s) References See Also Examples
This function provides a simple front-end to the boot
function in the
package also called boot
. Whereas boot
is very general and therefore
has many arguments, the Boot
function has very few arguments, but should
meet the needs of many users.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | ## Default S3 method:
Boot(object, f=coef, labels=names(coef(object)),
R=999, method=c("case", "residual"))
## S3 method for class 'lm'
Boot(object, f=coef, labels=names(coef(object)),
R=999, method=c("case", "residual"))
## S3 method for class 'glm'
Boot(object, f=coef, labels=names(coef(object)),
R=999, method=c("case", "residual"))
## S3 method for class 'nls'
Boot(object, f=coef, labels=names(coef(object)),
R=999, method=c("case", "residual"))
|
object |
A regression object of class |
f |
A function whose one argument is the name of a regression object that will be applied to the updated regression object to
compute the statistics of interest. The default is |
labels |
Provides labels for the statistics computed by |
R |
Number of bootstrap samples. The number of bootstrap samples actually computed may be smaller than
this value if either the fitting method is iterative, or if the rank of a fittle |
method |
The bootstrap method, either “case” for resampling
cases or “residuals” for a residual bootstrap. See the details
below. The residual bootstrap is available only for |
Whereas the boot
function is
very general, Boot
is very specific. It takes the information from a
regression object and the choice of method
, and creates a function that is
passed as the statistic
argument to boot
. The argument R
is also passed to boot
. All other arguments to boot
are
kept at their default values.
The methods available for lm
and nls
objects are “case” and
“residual”. The case bootstrap resamples from the joint distribution
of the terms in the model and the response. The residual bootstrap fixes the
fitted values from the original data, and creates bootstraps by adding a
bootstrap sample of the residuals to the fitted values to get a bootstrap
response. It is an implementation of Algorithm 6.3, page 271, of
Davison and Hinkley (1997). For nls
objects ordinary residuals are used
in the resampling rather than the standardized residuals used in the lm
method. The residual bootstrap for
generalized linear models has several competing approaches, but none are
without problems. If you want to do a residual bootstrap for a glm, you
will need to write your own call to boot
.
An attempt to model fit to a bootstrap sample may fail. In a lm
or
glm
fit, the bootstrap sample could have a different rank from the original
fit. In an nls
fit, convergence may not be obtained for some bootstraps.
In either case, NA
are returned for the value of the function f
.
The summary methods handle the NA
s appropriately.
See boot
for the returned value from this function. The car
package includes additional generic functions summary, confint and hist that works
with boot objects.
Sanford Weisberg, sandy@umn.edu.
Davison, A, and Hinkley, D. (1997) Bootstrap Methods and their Applications. Oxford: Oxford University Press.
Fox, J. and Weisberg, S. (2011) Companion to Applied Regression, Second Edition. Thousand Oaks: Sage.
Fox, J. and Weisberg, S. (2012) Bootstrapping, http://socserv.mcmaster.ca/jfox/Books/Companion/appendix/Appendix-Bootstrapping.pdf.
Weisberg, S. (2014) Applied Linear Regression, Fourth Edition, Wiley Wiley, Chapters 4 and 11.
Functions that work with
Boot
objects from the boot
package are
boot.array
,
boot.ci
,
plot.boot
and
empinf
. Additional
functions in the car
package are
summary.boot
,
confint.boot
, and
hist.boot
.
1 2 3 4 5 6 7 8 9 | m1 <- lm(Fertility ~ ., swiss)
betahat.boot <- Boot(m1, R=199) # 199 bootstrap samples--too small to be useful
summary(betahat.boot) # default summary
confint(betahat.boot)
hist(betahat.boot)
# Bootstrap for the estimated residual standard deviation:
sigmahat.boot <- Boot(m1, R=199, f=sigmaHat, labels="sigmaHat")
summary(sigmahat.boot)
confint(sigmahat.boot)
|
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