bootpred {bootstrap} R Documentation

## Bootstrap Estimates of Prediction Error

### Description

See Efron and Tibshirani (1993) for details on this function.

### Usage

   bootpred(x,y,nboot,theta.fit,theta.predict,err.meas,...)


### Arguments

 x a matrix containing the predictor (regressor) values. Each row corresponds to an observation. y a vector containing the response values nboot the number of bootstrap replications theta.fit function to be cross-validated. Takes x and y as an argument. See example below. theta.predict function producing predicted values for theta.fit. Arguments are a matrix x of predictors and fit object produced by theta.fit. See example below. err.meas function specifying error measure for a single response y and prediction yhat. See examples below ... any additional arguments to be passed to theta.fit

### Value

list with the following components

 app.err the apparent error rate - that is, the mean value of err.meas when theta.fit is applied to x and y, and then used to predict y. optim the bootstrap estimate of optimism in app.err. A useful estimate of prediction error is app.err+optim err.632 the ".632" bootstrap estimate of prediction error. call The deparsed call

### References

Efron, B. (1983). Estimating the error rate of a prediction rule: improvements on cross-validation. J. Amer. Stat. Assoc, vol 78. pages 316-31.

Efron, B. and Tibshirani, R. (1993) An Introduction to the Bootstrap. Chapman and Hall, New York, London.

### Examples

# bootstrap prediction error estimation in least squares
#  regression
x <- rnorm(85)
y <- 2*x +.5*rnorm(85)
theta.fit <- function(x,y){lsfit(x,y)}
theta.predict <- function(fit,x){
cbind(1,x)%*%fit\$coef
}
sq.err <- function(y,yhat) { (y-yhat)^2}
results <- bootpred(x,y,20,theta.fit,theta.predict,
err.meas=sq.err)

# for a classification problem, a standard choice
# for err.meas would simply count up the
#  classification errors:
miss.clas <- function(y,yhat){ 1*(yhat!=y)}
# with this specification,  bootpred estimates
#  misclassification rate


[Package bootstrap version 2019.6 Index]