Support zero variance when there are zero-variance predictions

[uriahf]

create_summary_report() does not work when there are zero-variance predictions.

This issue is similar to another issue about zero-variance outcomes: https://github.com/uriahf/rtichoke/issues/69

[uriahf]

• [x] Calibration Curve 1e44d70bcbdda384d8032b19d78e7fe86648bd02

These examples should work fine now

create_calibration_curve(
  probs = list(rep(0.23, 150)),
  reals = list(example_dat$outcome)
)

create_calibration_curve(
  probs = list(
    "First Model" = example_dat$estimated_probabilities,
    "Second Model" = rep(0.23, 150)
  ),
  reals = list(example_dat$outcome)
)

create_calibration_curve(
  probs = list(
    "train" = rep(0.23, 93),
    "test" = example_dat %>% dplyr::filter(type_of_set == "test") %>%
      dplyr::pull(estimated_probabilities)
  ),
  reals = list(
    "train" = example_dat %>% dplyr::filter(type_of_set == "train") %>%
      dplyr::pull(outcome),
    "test" = example_dat %>% dplyr::filter(type_of_set == "test") %>%
      dplyr::pull(outcome)
  )
)

• [x] Performance Table https://github.com/uriahf/rtichoke/commit/f458e4c51446a7c3565d2ada115b783bdc9c597c

These examples should work fine now

create_performance_table(
  probs = list(
    "Second Model" = rep(0.23, 150),
    "First Model" = example_dat$estimated_probabilities
  ),
  reals = list(example_dat$outcome), 
  stratified_by = "ppcr"
)

create_performance_table(
  probs = list(
    "Second Model" = rep(0.23, 150),
    "First Model" = example_dat$estimated_probabilities
  ),
  reals = list(example_dat$outcome)
) 

create_performance_table(
  probs = list(
    "train" = rep(0.23, 96),
    "test" = example_dat %>% dplyr::filter(type_of_set == "test") %>%
      dplyr::pull(estimated_probabilities)
  ),
  reals = list(
    "train" = example_dat %>% dplyr::filter(type_of_set == "train") %>%
      dplyr::pull(outcome),
    "test" = example_dat %>% dplyr::filter(type_of_set == "test") %>%
      dplyr::pull(outcome)
  ), 
  stratified_by = "ppcr"
)

• [x] Discrimination Curves https://github.com/uriahf/rtichoke/commit/6a1823d8d78475de7801a56f2ef2e87825af6fd2

These examples should work fine now

create_roc_curve(
  probs = list(rep(0.23, 150)),
  reals = list(example_dat$outcome),
  stratified_by = "ppcr"
)

create_roc_curve(
  probs = list(
    "First Model" = example_dat$estimated_probabilities,
    "Second Model" = rep(0.23, 150)
  ),
  reals = list(example_dat$outcome),
  stratified_by = "ppcr"
)

create_roc_curve(
  probs = list(
    "train" = rep(0.23, 93),
    "test" = example_dat %>% dplyr::filter(type_of_set == "test") %>%
      dplyr::pull(estimated_probabilities)
  ),
  reals = list(
    "train" = example_dat %>% dplyr::filter(type_of_set == "train") %>%
      dplyr::pull(outcome),
    "test" = example_dat %>% dplyr::filter(type_of_set == "test") %>%
      dplyr::pull(outcome)
  ),
  stratified_by = "ppcr"
)

• [x] Decision Curves