Description Usage Arguments Details Value Examples
View source: R/distance-depth.R
pulling out data points from curves that are ranked highest based on quantile function.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | quantile_curves_to_points(
x,
alpha,
dist_mat,
dist_func = distance_depth_function,
...
)
## S3 method for class 'list'
quantile_curves_to_points(
x,
alpha,
dist_mat,
dist_func = distance_depth_function,
...
)
## S3 method for class 'grouped_df'
quantile_curves_to_points(
x,
alpha,
dist_mat,
dist_func = distance_depth_function,
...
)
|
x |
list or grouped_df containing curves, with index ordering associated with the dist_mat's row ordering |
alpha |
the proportion of curves to be removed before presenting all the points together. Takes value in [0, 1.0]. |
dist_mat |
distance matrix |
dist_func |
function to calculate quantiles via the distance_matrix |
... |
additional parameters to be passed to the dist_func |
This function for lists (renamed as depth_curves_to_points
)
is shared with TCpredictionbands on github:
TCpredictionbands.
data frame from curves of the top values associated with the
dist_func
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | library(dplyr)
set.seed(1)
random_data_list <- lapply(1:5, function(x){data.frame(matrix(rnorm(10),
ncol = 2))})
dist_mat <- dist_matrix_innersq_direction(random_data_list,
position = 1:2,
verbose = FALSE)
combined_points_list <- quantile_curves_to_points(random_data_list,
alpha = .2,
dist_mat)
random_data_grouped <- random_data_list %>%
do.call(rbind, .) %>%
mutate(id = rep(1:5, each = 5)) %>%
group_by(id)
combined_points_grouped <- quantile_curves_to_points(random_data_grouped,
alpha = .2,
dist_mat)
|
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