# bootBCa

##### BCa Bootstrap on Existing Bootstrap Replicates

This functions constructs an object resembling one produced by the
`boot`

package's `boot`

function, and runs that package's
`boot.ci`

function to compute BCa and percentile confidence limits.
`bootBCa`

can provide separate confidence limits for a vector of
statistics when `estimate`

has length greater than 1. In that
case, `estimates`

must have the same number of columns as
`estimate`

has values.

- Keywords
- bootstrap

##### Usage

```
bootBCa(estimate, estimates, type=c('percentile','bca','basic'),
n, seed, conf.int = 0.95)
```

##### Arguments

- estimate
original whole-sample estimate

- estimates
vector of bootstrap estimates

- type
type of confidence interval, defaulting to nonparametric percentile

- n
original number of observations

- seed
`.Random.seem`

in effect before bootstrap estimates were run- conf.int
confidence level

##### Value

a 2-vector if `estimate`

is of length 1, otherwise a matrix
with 2 rows and number of columns equal to the length of
`estimate`

##### Note

You can use `if(!exists('.Random.seed')) runif(1)`

before running
your bootstrap to make sure that `.Random.seed`

will be available
to `bootBCa`

.

##### See Also

##### Examples

```
# NOT RUN {
x1 <- runif(100); x2 <- runif(100); y <- sample(0:1, 100, TRUE)
f <- lrm(y ~ x1 + x2, x=TRUE, y=TRUE)
seed <- .Random.seed
b <- bootcov(f)
# Get estimated log odds at x1=.4, x2=.6
X <- cbind(c(1,1), x1=c(.4,2), x2=c(.6,3))
est <- X <!-- %*% coef(b) -->
ests <- t(X <!-- %*% t(b$boot.Coef)) -->
bootBCa(est, ests, n=100, seed=seed)
bootBCa(est, ests, type='bca', n=100, seed=seed)
bootBCa(est, ests, type='basic', n=100, seed=seed)
# }
```

*Documentation reproduced from package rms, version 5.1-3.1, License: GPL (>= 2)*