derive_timeseries | R Documentation |
Derive the time series used in the AR1 model.
derive_timeseries(model, AR.start = NULL)
model |
GAMM model that includes an AR1 model. |
AR.start |
Vector with AR.start information, necessary for the AR1 model. Optional, defaults to NULL. |
A vector with time series indication based on the AR1 model.
Jacolien van Rij
Other functions for model criticism:
acf_n_plots()
,
acf_plot()
,
acf_resid()
,
resid_gam()
,
start_event()
,
start_value_rho()
data(simdat) # add missing values to simdat: simdat[sample(nrow(simdat), 15),]$Y <- NA simdat <- start_event(simdat, event=c('Subject', 'Trial')) ## Not run: # Run GAMM model: m1 <- bam(Y ~ te(Time, Trial)+s(Subject, bs='re'), data=simdat, rho=.5, AR.start=simdat$start.event) simdat$Event <- NA simdat[!is.na(simdat$Y),]$Event <- derive_timeseries(m1) acf_resid(m1, split_pred=list(Event=simdat$Event)) # And this works too: simdat$Event <- derive_timeseries(simdat$start.event) acf_resid(m1, split_pred=list(Event=simdat$Event)) # Note that acf_resid automatically makes use of derive_timeseries: acf_resid(m1, split_pred='AR.start') ## End(Not run)
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