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spaMM (version 1.9.16)

update.HLfit: Updates an HLCor or HLfit fit

Description

update will update and (by default) re-fit a model. It does this mostly by extracting the call stored in the object, updating the call and evaluating that call. (however, currently the predictor argument is processed differently). Using update is a risky programming style (see Note).

Usage

"update"(object, formula., ..., evaluate = TRUE)

Arguments

object
A return object from an HLfit call.
formula.
Changes to the formula. Beware of the syntax: see update.formula for details.
...
Additional arguments to the call, or arguments with changed values. Use name = NULL to remove the argument name.
evaluate
If TRUE, evaluate the new call else return the call.

Value

An HLCor or HLfit fit of the same type as the input object.

See Also

See also HLCor, HLfit.

Examples

Run this code
data(wafers)
## First the fit to be updated:
wFit <- HLfit(y ~X1*X3+X2*X3+I(X2^2)+(1|batch),family=Gamma(log),
          resid.model = ~ X3+I(X3^2) ,data=wafers)

# For estimates given by Lee et al., Appl. Stochastic Models Bus. Ind. (2011) 27:  315-328:
# Refit with given beta or/and phi values:
 
betavals <- c(5.55,0.08,-0.14,-0.21,-0.08,-0.09,-0.09)
# reconstruct fitted phi value from predictor for log(phi)
Xphi <- with(wafers,cbind(1,X3,X3^2)) ## design matrix
phifit <- exp(Xphi %*% c(-2.90,0.1,0.95))
update(wFit,formula.= . ~ offset(wFit$`X.pv` %*% betavals)+(1|batch),
       ranFix=list(lambda=exp(-3.67),phi=phifit))

## There are subtlety in performing REML fits of constrained models: 
update(wFit,formula.= . ~ offset(wFit$`X.pv` %*% betavals)+(1|batch))
## ... changes the REML correction. Consider instead
update(wFit,formula.= . ~ offset(wFit$`X.pv` %*% betavals)+(1|batch),
       REMLformula=wFit$predictor)
## Alternatively, show original wFit as differences from betavals:  
update(wFit,formula.= . ~ . +offset(wFit$`X.pv` %*% betavals))

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