```
context("general_T and general_forecasting.T work correctly")
test_that("general_T", {
# The value of the dependent variable of the following samples mediates
# in the stackloss dataset.
stackloss_center <- stackloss[c(9, 10, 11, 20, 21), ]
# The following samples are data other than the unit space data and the test
# data.
stackloss_signal <- stackloss[-c(2, 9, 10, 11, 12, 19, 20, 21), ]
# The following settings are same as the T1 method.
model <- general_T(unit_space_data = stackloss_center,
signal_space_data = stackloss_signal,
generates_transform_functions =
generates_transformation_functions_T1,
subtracts_V_e = TRUE,
includes_transformed_data = TRUE)
correct_M_hat <- c(26.750, 19.845, 8.668, 5.258, 6.963, 9.080, 9.080, -4.755,
-2.296, -9.977, -10.183, -9.438, -8.958)
expect_equal(round(as.vector(model$M_hat), 3), correct_M_hat)
})
test_that("general_forecasting.T without passing newdata", {
# The value of the dependent variable of the following samples mediates
# in the stackloss dataset.
stackloss_center <- stackloss[c(9, 10, 11, 20, 21), ]
# The following samples are data other than the unit space data and the test
# data.
stackloss_signal <- stackloss[-c(2, 9, 10, 11, 12, 19, 20, 21), ]
# The following settings are same as the T1 method.
model <- general_T(unit_space_data = stackloss_center,
signal_space_data = stackloss_signal,
generates_transform_functions =
generates_transformation_functions_T1,
subtracts_V_e = TRUE,
includes_transformed_data = TRUE)
forecasting <- general_forecasting.T(model = model,
includes_transformed_newdata = TRUE)
correct_M_hat <- c(26.750, 19.845, 8.668, 5.258, 6.963, 9.080, 9.080, -4.755,
-2.296, -9.977, -10.183, -9.438, -8.958)
expect_equal(round(as.vector(forecasting$M_hat), 3), correct_M_hat)
})
test_that("general_forecasting.T with passing newdata", {
# The value of the dependent variable of the following samples mediates
# in the stackloss dataset.
stackloss_center <- stackloss[c(9, 10, 11, 20, 21), ]
# The following samples are data other than the unit space data and the test
# data.
stackloss_signal <- stackloss[-c(2, 9, 10, 11, 12, 19, 20, 21), ]
# The following settings are same as the T1 method.
model <- general_T(unit_space_data = stackloss_center,
signal_space_data = stackloss_signal,
generates_transform_functions =
generates_transformation_functions_T1,
subtracts_V_e = TRUE,
includes_transformed_data = TRUE)
# The following test samples are chosen casually.
stackloss_test <- stackloss[c(2, 12, 19), -4]
forecasting <- general_forecasting.T(model = model,
newdata = stackloss_test,
includes_transformed_newdata = TRUE)
correct_y_hat <- c(41.281,8.552, 7.416)
expect_equal(round(as.numeric(forecasting$y_hat), 3), correct_y_hat)
})
```

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