# Linearly re-parameterize the model to be less sensitive to rounding errors

Source:`R/precondition.R`

`preconditionFit.Rd`

Linearly re-parameterize the model to be less sensitive to rounding errors

## Usage

`preconditionFit(fit, estType = c("full", "posthoc", "none"), ntry = 10L)`

## Arguments

- fit
A nlmixr2 fit to be preconditioned

- estType
Once the fit has been linearly reparameterized, should a "full" estimation, "posthoc" estimation or simply a estimation of the covariance matrix "none" before the fit is updated

- ntry
number of tries before giving up on a pre-conditioned covariance estimate