Code
ww_global_moran_i_vec(worldclim_predicted$response, tail(worldclim_predicted$
predicted, -1), worldclim_weights)
Condition
Error in `yardstick_vec()`:
! Length of `truth` (10000) and `estimate` (9999) must match.
Code
ww_global_moran_i_vec(tail(worldclim_predicted$response, -1),
worldclim_predicted$predicted, worldclim_weights)
Condition
Error in `yardstick_vec()`:
! Length of `truth` (9999) and `estimate` (10000) must match.
Code
ww_global_moran_i(worldclim_predicted, predicted, response)
Condition
Error in `ww_global_moran_i()`:
! `truth` must be numeric.
Code
ww_global_moran_i(worldclim_predicted, response, predicted)
Condition
Error in `ww_global_moran_i()`:
! `estimate` must be numeric.
Code
ww_global_moran_i_vec(worldclim_predicted$response, worldclim_predicted$
predicted, worldclim_weights)
Condition
Error in `yardstick_vec()`:
! `estimate` must be numeric.
Code
ww_global_moran_i_vec(worldclim_predicted$predicted, worldclim_predicted$
response, worldclim_weights)
Condition
Error in `yardstick_vec()`:
! `truth` must be numeric.
Code
ww_global_moran_i(worldclim_predicted, response, predicted)
Condition
Error in `ww_global_moran_i()`:
! `estimate` must be numeric.
Code
ww_global_moran_i(worldclim_predicted, predicted, response)
Condition
Error in `ww_global_moran_i()`:
! `truth` must be numeric.
Code
ww_global_moran_i(worldclim_predicted, predicted, response)$.estimate
Condition
Error in `spatial_yardstick_df()`:
! Missing values in data.
i waywiser can't handle missing data for functions that use spatial weights.
Code
ww_global_moran_i(worldclim_predicted, response, predicted)$.estimate
Condition
Error in `spatial_yardstick_df()`:
! Missing values in data.
i waywiser can't handle missing data for functions that use spatial weights.
Code
ww_global_moran_i_vec(worldclim_predicted$predicted, worldclim_predicted$
response, worldclim_weights)
Condition
Error in `spatial_yardstick_vec()`:
! Missing values in data.
i waywiser can't handle missing data for functions that use spatial weights.
Code
ww_global_moran_i_vec(worldclim_predicted$response, worldclim_predicted$
predicted, worldclim_weights)
Condition
Error in `spatial_yardstick_vec()`:
! Missing values in data.
i waywiser can't handle missing data for functions that use spatial weights.
Code
ww_global_moran_i_vec(numeric(), numeric(), structure(list(), class = "listw"))
Condition
Error in `yardstick_vec()`:
! 0 non-missing values were passed to `truth`.
Code
ww_global_moran_i(head(worldclim_predicted, 0), response, predicted, structure(
list(), class = "listw"))
Condition
Error in `ww_global_moran_i()`:
! 0 non-missing values were passed to `truth`.
Code
ww_global_moran_i(head(worldclim_predicted, 0), predicted, response, structure(
list(), class = "listw"))
Condition
Error in `ww_global_moran_i()`:
! 0 non-missing values were passed to `truth`.
Code
ww_global_moran_i_vec(NA_real_, NA_real_, structure(list(neighbours = 1),
class = "listw"))
Condition
Error in `spatial_yardstick_vec()`:
! Missing values in data.
i waywiser can't handle missing data for functions that use spatial weights.
Code
ww_global_moran_i(worldclim_predicted, response, predicted)$.estimate
Condition
Error in `spatial_yardstick_df()`:
! Missing values in data.
i waywiser can't handle missing data for functions that use spatial weights.
Code
ww_global_moran_i(worldclim_predicted, predicted, response)$.estimate
Condition
Error in `spatial_yardstick_df()`:
! Missing values in data.
i waywiser can't handle missing data for functions that use spatial weights.
Code
ww_global_moran_i_vec(worldclim_simulation$response, worldclim_simulation$
response, worldclim_weights)
Output
[1] NaN
Code
ww_global_moran_i(worldclim_simulation, response, response)
Output
# A tibble: 1 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 global_moran_i standard NaN
Code
withr::with_seed(123, ww_global_moran_i(worldclim_loaded, bio13, bio19))
Output
# A tibble: 1 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 global_moran_i standard 0.923
Code
withr::with_seed(123, ww_global_moran_i(worldclim_loaded, bio13, bio19))
Output
# A tibble: 1 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 global_moran_i standard 0.923
Code
withr::with_seed(123, ww_global_moran_i_vec(worldclim_loaded$bio13,
worldclim_loaded$bio19, worldclim_weights))
Output
[1] 0.9227199
Code
withr::with_seed(123, ww_global_moran_i_vec(worldclim_loaded$bio13,
worldclim_loaded$bio19, worldclim_weights))
Output
[1] 0.9227199
Code
withr::with_seed(123, ww_global_moran_i(worldclim_loaded, bio13, bio19))
Output
# A tibble: 1 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 global_moran_i standard 0.923
Code
withr::with_seed(123, ww_global_moran_i(worldclim_loaded, bio13, bio19,
function(data) ww_build_weights(ww_make_point_neighbors(data, k = 5))))
Output
# A tibble: 1 x 3
.metric .estimator .estimate
<chr> <chr> <dbl>
1 global_moran_i standard 0.833
Code
withr::with_seed(123, ww_global_moran_i_vec(worldclim_loaded$bio13,
worldclim_loaded$bio19, other_weights))
Output
[1] 0.8327575
Code
withr::with_seed(123, ww_global_moran_i_vec(worldclim_loaded$bio13,
worldclim_loaded$bio19, other_weights))
Output
[1] 0.8327575
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