Create a vector containing sets of quantiles — quantile

quantile_pred() is a special vector class used to efficiently store predictions from a quantile regression model. It requires the same quantile levels for each row being predicted.

Usage

quantile_pred(values, quantile_levels = double())

is_quantile_pred(x)

extract_quantile_levels(x)

# S3 method for class 'quantile_pred'
as_tibble(x, ..., .rows = NULL, .name_repair = "minimal", rownames = NULL)

# S3 method for class 'quantile_pred'
as.matrix(x, ...)

Arguments

values: A matrix of values. Each column should correspond to one of the quantile levels.
quantile_levels: A vector of probabilities corresponding to values.
x: An object produced by quantile_pred().
...: Not currently used.
.rows, .name_repair, rownames: Arguments not used but required by the original S3 method.

Value

quantile_pred() returns a vector of values associated with the quantile levels.
extract_quantile_levels() returns a numeric vector of levels.
as_tibble() returns a tibble with rows ".pred_quantile", ".quantile_levels", and ".row".
as.matrix() returns an unnamed matrix with rows as samples, columns as quantile levels, and entries are predictions.
is_quantile_pred() tests for the "quantile_pred" class

Examples

.pred_quantile <- quantile_pred(matrix(rnorm(20), 5), c(.2, .4, .6, .8))

unclass(.pred_quantile)
#> $quantile_values
#>            [,1]       [,2]       [,3]       [,4]
#> [1,]  0.5747557 -0.4755931 -2.1800396 -1.0686427
#> [2,] -1.0236557 -0.7094400 -1.3409932 -0.8553646
#> [3,] -0.0151383 -0.5012581 -0.2942939 -0.2806230
#> [4,] -0.9359486 -1.6290935 -0.4658975 -0.9943401
#> [5,]  1.1022975 -1.1676193  1.4494963 -0.9685143
#> 
#> attr(,"quantile_levels")
#> [1] 0.2 0.4 0.6 0.8

# Access the underlying information
extract_quantile_levels(.pred_quantile)
#> [1] 0.2 0.4 0.6 0.8

# Matrix format
as.matrix(.pred_quantile)
#>            [,1]       [,2]       [,3]       [,4]
#> [1,]  0.5747557 -0.4755931 -2.1800396 -1.0686427
#> [2,] -1.0236557 -0.7094400 -1.3409932 -0.8553646
#> [3,] -0.0151383 -0.5012581 -0.2942939 -0.2806230
#> [4,] -0.9359486 -1.6290935 -0.4658975 -0.9943401
#> [5,]  1.1022975 -1.1676193  1.4494963 -0.9685143

# Tidy format
library(tibble)
as_tibble(.pred_quantile)
#> # A tibble: 20 × 3
#>    .pred_quantile .quantile_levels  .row
#>             <dbl>            <dbl> <int>
#>  1         0.575               0.2     1
#>  2        -0.476               0.4     1
#>  3        -2.18                0.6     1
#>  4        -1.07                0.8     1
#>  5        -1.02                0.2     2
#>  6        -0.709               0.4     2
#>  7        -1.34                0.6     2
#>  8        -0.855               0.8     2
#>  9        -0.0151              0.2     3
#> 10        -0.501               0.4     3
#> 11        -0.294               0.6     3
#> 12        -0.281               0.8     3
#> 13        -0.936               0.2     4
#> 14        -1.63                0.4     4
#> 15        -0.466               0.6     4
#> 16        -0.994               0.8     4
#> 17         1.10                0.2     5
#> 18        -1.17                0.4     5
#> 19         1.45                0.6     5
#> 20        -0.969               0.8     5