Nothing
test_that("yc_svensson fits a curve", {
d <- make_us_yields()
fit <- yc_svensson(d$maturities, d$rates)
expect_s3_class(fit, "yc_curve")
expect_equal(fit$method, "svensson")
expect_true(all(c("beta0", "beta1", "beta2", "beta3", "tau1", "tau2") %in%
names(fit$params)))
})
test_that("yc_svensson fits at least as well as nelson_siegel", {
d <- make_us_yields()
ns_fit <- yc_nelson_siegel(d$maturities, d$rates)
sv_fit <- yc_svensson(d$maturities, d$rates)
ns_rmse <- sqrt(mean(ns_fit$residuals^2))
sv_rmse <- sqrt(mean(sv_fit$residuals^2))
# Svensson has more parameters, should fit at least as well
expect_true(sv_rmse <= ns_rmse + 1e-6)
})
test_that("yc_svensson warns with fewer than 6 points", {
expect_warning(
yc_svensson(c(1, 2, 5, 10), c(0.04, 0.042, 0.043, 0.045)),
"fewer than 6"
)
})
test_that("yc_svensson known-value recovery", {
# Generate synthetic data from known Svensson parameters
beta0 <- 0.06
beta1 <- -0.02
beta2 <- 0.01
beta3 <- -0.005
tau1 <- 2
tau2 <- 5
m <- c(0.25, 0.5, 1, 2, 3, 5, 7, 10, 20, 30)
# Svensson formula
f1 <- (1 - exp(-m / tau1)) / (m / tau1)
f2 <- f1 - exp(-m / tau1)
f3 <- (1 - exp(-m / tau2)) / (m / tau2) - exp(-m / tau2)
synthetic_rates <- beta0 + beta1 * f1 + beta2 * f2 + beta3 * f3
fit <- yc_svensson(m, synthetic_rates, tau1_init = 2, tau2_init = 5)
rmse <- sqrt(mean(fit$residuals^2))
expect_true(rmse < 0.001)
})
test_that("yc_svensson handles negative rates", {
m <- c(0.5, 1, 2, 5, 7, 10, 20, 30)
rates <- c(-0.005, -0.004, -0.003, -0.001, 0.001, 0.003, 0.005, 0.006)
fit <- yc_svensson(m, rates)
expect_s3_class(fit, "yc_curve")
rmse <- sqrt(mean(fit$residuals^2))
expect_true(rmse < 0.005)
})
test_that("yc_svensson rejects bad inputs", {
expect_error(yc_svensson("a", 0.04), "numeric")
expect_error(yc_svensson(c(1, 2), c(0.04, 0.05), tau1_init = -1), "positive")
expect_error(yc_svensson(c(1, 2), c(0.04, 0.05), tau2_init = 0), "positive")
})
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