# estfun.maxLik: Extract Gradients Evaluated at each Observation In maxLik: Maximum Likelihood Estimation and Related Tools

## Description

Extract the gradients of the log-likelihood function evaluated at each observation (‘Empirical Estimating Function’, see `estfun`).

## Usage

 ```1 2``` ```## S3 method for class 'maxLik' estfun( x, ... ) ```

## Arguments

 `x` an object of class `maxLik`. `...` further arguments (currently ignored).

## Value

Matrix of log-likelihood gradients at the estimated parameter value evaluated at each observation. Observations in rows, parameters in columns.

## Warnings

The sandwich package must be loaded before this method can be used.

This method works only if the observaton-specific gradient information was available for the estimation. This is the case of the observation-specific gradient was supplied (see the `grad` argument for `maxLik`), or the log-likelihood function returns a vector of observation-specific values.

## Author(s)

Arne Henningsen

`estfun`, `maxLik`.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```## ML estimation of exponential duration model: t <- rexp(100, 2) loglik <- function(theta) log(theta) - theta*t ## Estimate with numeric gradient and hessian a <- maxLik(loglik, start=1 ) # Extract the gradients evaluated at each observation library( sandwich ) head(estfun( a ), 10) ## Estimate with analytic gradient. ## Note: it returns a vector gradlik <- function(theta) 1/theta - t b <- maxLik(loglik, gradlik, start=1) head(estfun( b ), 10) ```

### Example output

```Loading required package: miscTools

Please cite the 'maxLik' package as:
Henningsen, Arne and Toomet, Ott (2011). maxLik: A package for maximum likelihood estimation in R. Computational Statistics 26(3), 443-458. DOI 10.1007/s00180-010-0217-1.

If you have questions, suggestions, or comments regarding the 'maxLik' package, please use a forum or 'tracker' at maxLik's R-Forge site:
https://r-forge.r-project.org/projects/maxlik/
[,1]
[1,]  0.27358194
[2,]  0.43449741
[3,]  0.09444664
[4,]  0.39167460
[5,]  0.14650982
[6,] -0.61657145
[7,]  0.10828263
[8,]  0.06367943
[9,]  0.24525371
[10,] -1.02765669
[,1]
[1,]  0.27358194
[2,]  0.43449741
[3,]  0.09444664
[4,]  0.39167460
[5,]  0.14650982
[6,] -0.61657145
[7,]  0.10828263
[8,]  0.06367943
[9,]  0.24525371
[10,] -1.02765669
```

maxLik documentation built on May 30, 2017, 1:07 a.m.