R Under development (unstable) (2024-09-21 r87186 ucrt) -- "Unsuffered Consequences"
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> 
> library("mlt")
Loading required package: basefun
Loading required package: variables
> library("survival")
> 
> set.seed(290875)
> 
> chk <- function(x, y) stopifnot(all.equal(x, y, tol = 1e-4, check.attributes = FALSE))
> 
> ### check -Inf, Inf interval censoring for handling missing
> ### response values
> ### numeric response
> N <- 100
> x <- rnorm(N)
> ina <- sample(1:length(x))[1:floor(N / 10)]
> x[ina] <- NA
> 
> d <- data.frame(x = x)
> d$Rx <- d$Rxi <- R(x)
> d$Rxi$cleft <- -Inf
> d$Rxi$cright <- Inf
> d$Rx2 <- R(x, as.R.interval = TRUE)
> 
> m <- mlt(ctm(response = Bernstein_basis(numeric_var("x"), order = 1)),
+          data = d[-ina,,drop = FALSE])
> mx <- mlt(ctm(response = Bernstein_basis(numeric_var("x"), order = 1)),
+           data = d)
> mRx <- mlt(ctm(response = Bernstein_basis(numeric_var("Rx"), order = 1)),
+            data = d)
> mRxi <- mlt(ctm(response = Bernstein_basis(numeric_var("Rxi"), order = 1)),
+             data = d)
> mRx2 <- mlt(ctm(response = Bernstein_basis(numeric_var("Rx2"), order = 1)),
+             data = d)
> mx2 <- mlt(ctm(response = Bernstein_basis(numeric_var("Rx2"), order = 1)),
+            data = d[-ina,,drop = FALSE])
> 
> chk(coef(mx), coef(m))
> chk(coef(mRx), coef(m))
> chk(coef(mRxi), coef(m))
> 
> chk(logLik(mx), logLik(m))
> chk(logLik(mRx), logLik(m))
> chk(logLik(mRxi), logLik(m))
> 
> chk(coef(mRx2), coef(mx2))
> 
> chk(logLik(mRx2), logLik(mx2))
> 
> ### ordered factors
> x <- gl(4, N, ordered = TRUE)
> x[ina] <- NA
> d <- data.frame(x = x)
> 
> m <- mlt(ctm(response = as.basis(d$x)),
+          data = d[-ina,,drop = FALSE])
> 
> mx <- mlt(ctm(response = as.basis(d$x)),
+           data = d)
> 
> chk(coef(m), coef(mx))
> 
> chk(logLik(m), logLik(mx))
> 
> ### integers
> x <- sample(1:N)
> x[ina] <- NA
> d <- data.frame(x = x)
> d$Rx <- R(x)
> 
> mx <- mlt(ctm(response = Bernstein_basis(numeric_var("Rx"), order = 1)),
+           data = d)
> 
> mx2 <- mlt(ctm(response = Bernstein_basis(numeric_var("Rx"), order = 1)),
+            data = d[-ina,,drop = FALSE])
> 
> chk(coef(mx), coef(mx2))
> 
> chk(logLik(mx), logLik(mx2))
> 
> ### survival
> x <- exp(rnorm(N))
> x[ina] <- NA
> 
> ### right censoring
> d <- data.frame(y = Surv(x, event = x > 1))
> tol <- sqrt(.Machine$double.eps)
> m <- mlt(ctm(response = Bernstein_basis(
+     numeric_var("y", bounds = c(tol, Inf), support = c(tol, 10)), 
+     order = 1, log_first = TRUE)),
+     data = d[-ina,,drop = FALSE])
> mx <- mlt(ctm(response = Bernstein_basis(
+     numeric_var("y", bounds = c(tol, Inf), support = c(tol, 10)), 
+     order = 1, log_first = TRUE)),
+     data = d)
> 
> chk(coef(m), coef(mx))
> 
> chk(logLik(m), logLik(mx))
> 
> ### left censoring
> d <- data.frame(y = Surv(x, event = x > 1, type = "left"))
> tol <- sqrt(.Machine$double.eps)
> m <- mlt(ctm(response = Bernstein_basis(
+     numeric_var("y", bounds = c(tol, Inf), support = c(tol, 10)), 
+     order = 1, log_first = TRUE)),
+     data = d[-ina,,drop = FALSE])
> mx <- mlt(ctm(response = Bernstein_basis(
+     numeric_var("y", bounds = c(tol, Inf), support = c(tol, 10)), 
+     order = 1, log_first = TRUE)),
+     data = d)
> 
> chk(coef(m), coef(mx))
> 
> chk(logLik(m), logLik(mx))
> 
> ### empirical likelihood
> d$y <- R(Surv(x, event = x > 1), as.R.interval = TRUE)
> m <- mlt(ctm(response = Bernstein_basis(
+     numeric_var("y", bounds = c(tol, Inf), support = c(tol, 10)), 
+     order = 1, log_first = TRUE)),
+     data = d[-ina,,drop = FALSE])
> mx <- mlt(ctm(response = Bernstein_basis(
+     numeric_var("y", bounds = c(tol, Inf), support = c(tol, 10)), 
+     order = 1, log_first = TRUE)),
+     data = d)
> 
> chk(coef(m), coef(mx))
> 
> chk(logLik(m), logLik(mx))
> 
> proc.time()
   user  system elapsed 
   2.06    0.32    2.32