# trafoEst: Function trafoEst in Package 'distrMod' In distrMod: Object Oriented Implementation of Probability Models

## Description

`trafoEst` takes a tau like function (compare `trafo-methods`) and transforms an existing estimator by means of this transformation.

## Usage

 `1` ```trafoEst(fct, estimator) ```

## Arguments

 `fct` a tau like function, i.e., a function in the main part theta of the parameter returning a list `list(fval, mat)` where `fval` is the function value tau(theta) of the transformation, and `mat`, its derivative matrix at theta. `estimator` an object of class `Estimator`.

## Details

The disadvantage of this proceeding is that the transformation is not accounted for in determining the estimate (e.g. in a corresponding optimality); it simply transforms an existing estimator, without reapplying it to data. This becomes important in optimally robust estimation.

## Value

exactly the argument `estimator`, but with modified slots `estimate`, `asvar`, and `trafo`.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24``` ```## Gaussian location and scale NS <- NormLocationScaleFamily(mean=2, sd=3) ## generate data out of this situation x <- r(distribution(NS))(30) ## want to estimate mu/sigma, sigma^2 ## -> without new trafo slot: mtrafo <- function(param){ mu <- param["mean"] sd <- param["sd"] fval <- c(mu/sd, sd^2) nfval <- c("mu/sig", "sig^2") names(fval) <- nfval mat <- matrix(c(1/sd,0,-mu/sd^2,2*sd),2,2) dimnames(mat) <- list(nfval,c("mean","sd")) return(list(fval=fval, mat=mat)) } ## Maximum likelihood estimator in the original problem res0 <- MLEstimator(x = x, ParamFamily = NS) ## transformation res <- trafoEst(mtrafo, res0) ## confidence interval confint(res) ```

distrMod documentation built on April 15, 2017, 11:09 a.m.