Nothing
test_that("predict handles normal-nig latent noise", {
withr::local_seed(1)
n <- 12
data <- data.frame(
y = as.numeric(arima.sim(list(ar = 0.4), n = n)),
idx = seq_len(n)
)
fit <- ngme(
y ~ 0 + f(idx, model = ar1(), noise = noise_normal_nig(), name = "latent"),
data = data,
control_opt = control_opt(
iterations = 30,
n_batch = 3,
n_min_batch = 1,
burnin = 1,
verbose = FALSE,
print_check_info = FALSE,
store_traj = FALSE,
seed = 1
)
)
pred_latent <- predict(
fit,
map = list(latent = data$idx),
type = "latent",
estimator = c("mean", "sd", "0.025q", "0.975q"),
sampling_size = 10,
burnin_size = 2,
seed = 1
)
pred_response <- predict(
fit,
map = list(latent = data$idx),
type = "response",
estimator = c("mean", "sd"),
sampling_size = 10,
burnin_size = 2,
seed = 1
)
pred_latent_samples <- predict(
fit,
map = list(latent = data$idx),
type = "latent",
estimator = c("mean", "sd", "0.025q", "0.975q"),
sampling_size = 10,
burnin_size = 2,
seed = 1,
return_samples = TRUE
)
expect_length(pred_latent$mean, n)
expect_length(pred_response$mean, n)
expect_length(pred_response$sd, n)
expect_true(all(is.finite(pred_latent$mean)))
expect_true(all(is.finite(pred_response$mean)))
expect_true(all(is.finite(pred_response$sd)))
expect_equal(pred_latent$mean, pred_latent_samples$mean)
expect_equal(pred_latent$sd, pred_latent_samples$sd)
expect_equal(pred_latent$`0.025q`, pred_latent_samples$`0.025q`)
expect_equal(pred_latent$`0.975q`, pred_latent_samples$`0.975q`)
})
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