# lmrob..D..fit: Compute Design Adaptive Scale estimate In robustbase: Basic Robust Statistics

 lmrob..D..fit R Documentation

## Compute Design Adaptive Scale estimate

### Description

This function calculates a Design Adaptive Scale estimate for a given MM-estimate. This is supposed to be a part of a chain of estimates like `SMD` or `SMDM`.

### Usage

``````lmrob..D..fit(obj, x=obj\$x, control = obj\$control,
mf,
method = obj\$control\$method)
``````

### Arguments

 `obj` `lmrob`-object based on which the estimate is to be calculated. `x` the design matrix; if `missing`, the method tries to get it from `obj\$x` and if this fails from `obj\$model`. `control` list of control parameters, as returned by `lmrob.control`. `mf` defunct. `method` optional; the `method` used for obj computation.

### Details

This function is used by `lmrob.fit` and typically not to be used on its own. Note that `lmrob.fit()` specifies `control` potentially differently than the default, but does use the default for `method`.

### Value

The given `lmrob`-object with the following elements updated:

 `scale` The Design Adaptive Scale estimate `converged` `TRUE` if the scale calculation converged, `FALSE` other.

Manuel Koller

### References

Koller, M. and Stahel, W.A. (2011), Sharpening Wald-type inference in robust regression for small samples, Computational Statistics & Data Analysis 55(8), 2504–2515.

`lmrob.fit`, `lmrob`

### Examples

``````data(stackloss)
## Compute manual SMD-estimate:
## 1) MM-estimate
m1 <- lmrob(stack.loss ~ ., data = stackloss)