bootBCa

This functions constructs an object resembling one produced by the
<code>boot</code> package's <code>boot</code> function, and runs that package's
<code>boot.ci</code> function to compute BCa and percentile confidence limits.
<code>bootBCa</code> can provide separate confidence limits for a vector of
statistics when <code>estimate</code> has length greater than 1. In that
case, <code>estimates</code> must have the same number of columns as
<code>estimate</code> has values.

bootstrap

Regression modeling, testing, estimation, validation,
graphics, prediction, and typesetting by storing enhanced model design
attributes in the fit.  'rms' is a collection of functions that
assist with and streamline modeling.  It also contains functions for
binary and ordinal logistic regression models, ordinal models for
continuous Y with a variety of distribution families, and the Buckley-James
multiple regression model for right-censored responses, and implements
penalized maximum likelihood estimation for logistic and ordinary
linear models.  'rms' works with almost any regression model, but it
was especially written to work with binary or ordinal regression
models, Cox regression, accelerated failure time models,
ordinary linear models,	the Buckley-James model, generalized least
squares for serially or spatially correlated observations, generalized
linear models, and quantile regression.

Frank Harrell Jr

Regression Modeling Strategies

bootBCa function

<dl> <dt>estimate</dt>
<dd>original whole-sample estimate</dd> <dt>estimates</dt>
<dd>vector of bootstrap estimates</dd> <dt>type</dt>
<dd>type of confidence interval, defaulting to nonparametric
	percentile</dd> <dt>n</dt>
<dd>original number of observations</dd> <dt>seed</dt>
<dd><code>.Random.seem</code> in effect before bootstrap estimates
	were run</dd> <dt>conf.int</dt>
<dd>confidence level</dd></dl>

Arguments

Author

BCa Bootstrap on Existing Bootstrap Replicates — bootBCa

<dl>

 <dt>estimate</dt>
<dd>original whole-sample estimate</dd>

 <dt>estimates</dt>
<dd>vector of bootstrap estimates</dd>

 <dt>type</dt>
<dd>type of confidence interval, defaulting to nonparametric
	percentile</dd>

 <dt>n</dt>
<dd>original number of observations</dd>

 <dt>seed</dt>
<dd><code>.Random.seem</code> in effect before bootstrap estimates
	were run</dd>

 <dt>conf.int</dt>
<dd>confidence level</dd>

</dl>

bootBCa: BCa Bootstrap on Existing Bootstrap Replicates

Description

Usage

Value

Arguments

Author

See Also