spaMM (version 3.2.0)

update.HLfit: Updates a fit

Description

update and update_resp will update and (by default) re-fit a model. They do this mostly by extracting the call stored in the object, updating the call and evaluating that call. Using update is a risky programming style (see Note). update_resp handles a new response vector as produced by simulate.

Usage

# S3 method for HLfit
update(object, formula., ..., evaluate = TRUE)
update_resp(object, newresp, ..., 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.

newresp

New response vector.

…

Additional arguments to the call, or arguments with changed values. Use name = NULL to remove the argument with given name.

evaluate

If TRUE, evaluate the new call else return the call.

Value

An HLfit fit of the same type as the input object, or a call object, depending on the evaluate value.

See Also

See also HLCor, HLfit.

Examples

# NOT RUN {
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)

newresp <- simulate(wFit)
update_resp(wFit,newresp=newresp)

# 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))
upd_wafers <- wafers
upd_wafers$off_b <- wFit$`X.pv` %*% betavals
update(wFit,formula.= . ~ offset(off_b)+(1|batch), data=upd_wafers,
       ranFix=list(lambda=exp(-3.67),phi=phifit))

## There are subtlety in performing REML fits of constrained models,
##   illustrated by the fact that the following fit does not recover 
##   the original likelihood values, because dispersion parameters are
##   estimated but the REML correction changes with the formula:
upd_wafers$off_f <- wFit$`X.pv` %*% fixef(wFit) ## = predict(wFit,re.form=NA,type="link")
update(wFit,formula.= . ~ offset(off_f)+(1|batch), data=upd_wafers)
## To maintain the original REML correction, Consider instead
update(wFit,formula.= . ~ offset(off_f)+(1|batch), data=upd_wafers,
       REMLformula=formula(wFit))  ## recover original p_v and p_bv     
## Alternatively, show original wFit as differences from betavals:  
update(wFit,formula.= . ~ . +offset(off_f), data=upd_wafers)
# }