# EEF.profile {boot}

### Description

Construct the empirical log likelihood or empirical exponential family log likelihood for a mean.

### Usage

EEF.profile(y, tmin = min(y) + 0.1, tmax = max(y) - 0.1, n.t = 25, u = function(y, t) y - t) EL.profile(y, tmin = min(y) + 0.1, tmax = max(y) - 0.1, n.t = 25, u = function(y, t) y - t)

### Arguments

- y
- A vector or matrix of data
- tmin
- The minimum value of the range over which the likelihood should be computed. This must be larger than
`min(y)`

. - tmax
- The maximum value of the range over which the likelihood should be computed. This must be smaller than
`max(y)`

. - n.t
- The number of points between
`tmin`

and`tmax`

at which the value of the log-likelihood should be computed. - u
- A function of the data and the parameter.

### Details

These functions calculate the log likelihood for a mean using either an empirical likelihood or an empirical exponential family likelihood. They are supplied as part of the package `boot`

for demonstration purposes with the practicals in chapter 10 of Davison and Hinkley (1997). The functions are not intended for general use and are not supported as part of the `boot`

package. For more general and more robust code to calculate empirical likelihoods see Professor A. B. Owen's empirical likelihood home page at the URL http://statistics.stanford.edu/~owen/empirical/.

### Values

A matrix with `n.t`

rows. The first column contains the values of the parameter used. The second column of the output of `EL.profile`

contains the values of the empirical log likelihood. The second and third columns of the output of `EEF.profile`

contain two versions of the empirical exponential family log-likelihood. The final column of the output matrix contains the values of the Lagrange multiplier used in the optimization procedure.

### References

Davison, A. C. and Hinkley, D. V. (1997) *Bootstrap Methods and Their Application*. Cambridge University Press.

Documentation reproduced from package boot, version 1.3-17. License: Unlimited