Nothing
alpha <- -0.35
coefs <- c(0.0012, 0.029, 0.1, 0.15, 0.23, 0.0074, 0.052, 0.1)
knots <- c(0.36, 0.62, 0.91, 1.2, 1.54, 2.02, 3)
test_that("wane functions",{
pnw <- psurvmspline(q=c(10,14,18), alpha=alpha, coefs=coefs, knots=knots)
pw <- psurvmspline_wane(q=10, alpha1=alpha, alpha0=-0.2, coefs1=coefs, coefs0=coefs,
knots=knots, wane_period=c(11, 15))
hnw <- hsurvmspline(x=c(10,14,18), alpha=alpha, coefs=coefs, knots=knots)
expect_equal(hnw[1],hnw[3])
hw <- hsurvmspline_wane(x=c(10,14,18), alpha1=alpha, alpha0=-0.2, coefs1=coefs, coefs0=coefs,
knots=knots, wane_period=c(11, 15))
dnw <- dsurvmspline(x=10, alpha=alpha, coefs=coefs, knots=knots)
dw <- dsurvmspline_wane(x=10, alpha1=alpha, alpha0=-0.2, coefs1=coefs, coefs0=coefs,
knots=knots, wane_period=c(11, 15))
expect_equal(pnw[1], pw[1])
expect_equal(dnw[1], dw[1])
expect_equal(hnw[1], hw[1])
expect_lt(hnw[2], hw[2])
expect_lt(hnw[3], hw[3])
})
test_that("wane functions: vectorisation over parameters",{
h1 <- Hsurvmspline_wane(x=c(8, 10), alpha1=-1, alpha0=-2,
coefs1=coefs, coefs0=coefs, knots=knots, wane_period=c(9, 11))
h2 <- Hsurvmspline_wane(x=c(8, 10), alpha1=-3, alpha0=-4,
coefs1=coefs, coefs0=coefs, knots=knots, wane_period=c(9, 11))
h12 <- Hsurvmspline_wane(x=c(8, 10), alpha1=c(-1,-3), alpha0=c(-2,-4),
coefs1=coefs, coefs0=coefs, knots=knots, wane_period=c(9, 11))
expect_equal(h12, c(h1[1], h2[2]))
})
test_that("wane functions: vectorisation errors",{
expect_error(Hsurvmspline_wane(x=c(0, 8, 10, 12), alpha1=rep(alpha,2), alpha0=alpha*1.01,
coefs1=coefs, coefs0=coefs, knots=knots, wane_period=c(9, 11)),
"lengths of `alpha0`")
})
mod <- survextrap(Surv(years, status) ~ rx, data=colons, fit_method="opt")
test_that("default newdata0",{
nd <- data.frame(rx = c("Obs", "Lev+5FU"))
nd0 <- data.frame(rx = c("Obs", "Obs"))
rd <- rmst(mod, wane_period=c(2,3), t=7, niter=5, wane_nt=2)
rn <- rmst(mod, newdata0=nd0, newdata=nd, wane_period=c(2,3), t=7, niter=5, wane_nt=2)
expect_equal(rd$median[c(1,3)], rn$median, tol=1e-06)
})
test_that("rmst wane",{
rd <- rmst(mod, t=2, niter=5)
rd2 <- rmst(mod, t=2, wane_period=c(5,7), niter=5)
expect_equal(rd$median, rd2$median)
rd <- rmst(mod, t=5, niter=5)
rd2 <- rmst(mod, t=5, wane_period=c(3,5), niter=5)
expect_lt(rd2$median[2], rd$median[2])
})
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