## Executable examples are disabled for routine package builds. Set LKT_RUN_EXPENSIVE_VIGNETTES=true to run this vignette.The Wald model uses one normal trial-noise draw and a fixed participant speed effect. The Wald contamination allowance is used for fitting only, never generation.
set.seed(20261030)
sid <- rep(paste0("s",1:6),each=16)
d <- data.table::data.table(Anon.Student.Id=sid,
KC..Default.=rep(c("k1","k2"),48),
CF..ansbin.=rep(c(1,1,0,1,0,0,1,1),12),
CF..Time.=rep(seq(1000,1150,10),6),
Duration..sec.=rep(seq(3,25,length.out=16),6),fold=1L)
wald <- LKT(data.table::copy(d),components="KC..Default.",features="logitdec",
fixedpars=.9,interc=TRUE,dualfit=TRUE,distribution="Wald",verbose=FALSE,
wald_t0_fixed=0,wald_control=list(nodes=15L,maxit=120L))
check_true("Wald result",wald$model_specification[[2]]$distribution=="Wald")
check_true("Wald engaged generation",wald$model_specification[[2]]$generation=="engaged_only")
check_true("Wald finite prediction",all(is.finite(wald$latencymodel[[1]]$predict(c(.2,.5,.9),0,FALSE))))The usefolds and optional
latency_question_type_filter settings select fitting
observations. Excluded rows still contribute to the actual feature
histories. The retired exponential and Weibull latency choices are
deliberately rejected.