R Under development (unstable) (2024-11-28 r87392 ucrt) -- "Unsuffered Consequences"
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> ## ===== confband =====
> ## -- Test utils & settings
> source("test_util.R")
> .run_test <- identical(Sys.getenv("NOT_CRAN"), "true")
> oldopt <- options(digits = 4)
> set.seed(100)
> 
> library("tramME")
Loading required package: tram
Loading required package: mlt
Loading required package: basefun
Loading required package: variables
Loading required package: mvtnorm
> library("survival")
> 
> m_cars <- BoxCoxME(dist ~ speed, data = cars)
> 
> ## -- Consistency under various argument values
> pr1 <- confband(m_cars, newdata = data.frame(speed = c(0, 1)))
> pr2 <- confband(m_cars, newdata = NULL)
> pr3 <- confband(m_cars, newdata = data.frame(speed = c(0, 1)),
+                 baseline_only = TRUE)
> 
> chkeq(pr1[[1]], pr2, check.attributes = FALSE)
> chkeq(pr1[[1]], pr3[[2]], check.attributes = FALSE)
> 
> ## set q
> pr1 <- confband(m_cars, newdata = data.frame(speed = c(0, 1)),
+                        q = c(20, 40))
> 
> ## -- Consistency with predict
> data("sleepstudy", package = "lme4")
> m_sleep <- ColrME(Reaction ~ s(Days) + (Days | Subject), data = sleepstudy)
> 
> nd <- model.frame(m_sleep)[c(1, 171), ]
> cb <- confband(m_sleep, newdata = nd, K = 100, type = "distribution")
> re <- ranef(m_sleep)[[1]][c(1, 18), ]
> pr <- predict(m_sleep, newdata = nd[, -1L], ranef = c(t(re)),
+               K = 100, type = "distribution")
> chkeq(cb[[1]][, 2], pr[, 1], check.attributes = FALSE)
> chkeq(cb[[2]][, 2], pr[, 2], check.attributes = FALSE)
> 
> ## set q
> nd <- data.frame(dist = c(20, 40), speed = c(1, 1))
> pr2 <- predict(m_cars, newdata = nd, type = "trafo")
> chkeq(pr1[[2]][, 2], pr2, check.attributes = FALSE)
> 
> ## TODO -- Adjust
> ## pr1 <- confband.tramME(m_cars, newdata = data.frame(speed = c(0, 1)),
> ##                        adjust = TRUE, K = 100, cheat = 20)
> 
> summarize_tests()
==========================
Number of failed tests: 0
==========================
> 
> options(oldopt)
> 
> proc.time()
   user  system elapsed 
   2.17    0.18    2.36