R Under development (unstable) (2023-12-13 r85679 ucrt) -- "Unsuffered Consequences"
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> 
> # copied from ../man/aster.Rd examples section
> 
>  library(aster)
>  data(echinacea)
>  vars <- c("ld02", "ld03", "ld04", "fl02", "fl03", "fl04",
+      "hdct02", "hdct03", "hdct04")
>  redata <- reshape(echinacea, varying = list(vars), direction = "long",
+      timevar = "varb", times = as.factor(vars), v.names = "resp")
>  redata <- data.frame(redata, root = 1)
>  pred <- c(0, 1, 2, 1, 2, 3, 4, 5, 6)
>  fam <- c(1, 1, 1, 1, 1, 1, 3, 3, 3)
>  hdct <- grepl("hdct", as.character(redata$varb))
>  redata <- data.frame(redata, hdct = as.integer(hdct))
>  level <- gsub("[0-9]", "", as.character(redata$varb))
>  redata <- data.frame(redata, level = as.factor(level))
>  aout <- aster(resp ~ varb + level : (nsloc + ewloc) + hdct : pop,
+      pred, fam, varb, id, root, data = redata)
> 
> # redo with new function
> 
>  theta <- predict(aout, parm.type = "canonical", model.type = "conditional")
>  phi <- predict(aout, parm.type = "canonical", model.type = "unconditional")
> 
>  nind <- nrow(echinacea)
>  nnode <- length(pred)
> 
>  aster:::setfam(fam.default())
> 
>  val.theta <- .C(aster:::C_aster_export_exerciser,
+      nind = as.integer(nind),
+      nnode = as.integer(nnode),
+      pred = as.integer(pred),
+      fam = as.integer(fam),
+      parm = as.double(theta),
+      root = as.double(redata$root),
+      response = as.double(redata$resp),
+      is.unco = FALSE,
+      value = double(1))$value
> 
>  val.phi <- .C(aster:::C_aster_export_exerciser,
+      nind = as.integer(nind),
+      nnode = as.integer(nnode),
+      pred = as.integer(pred),
+      fam = as.integer(fam),
+      parm = as.double(phi),
+      root = as.double(redata$root),
+      response = as.double(redata$resp),
+      is.unco = TRUE,
+      value = double(1))$value
> 
>  aster:::clearfam()
> 
>  all.equal(val.theta, aout$deviance / 2)
[1] TRUE
>  all.equal(val.phi, aout$deviance / 2)
[1] TRUE
> 
> 
> proc.time()
   user  system elapsed 
   0.42    0.07    0.48