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Create a vector containing sets of quantiles

Source: R/quantile-pred.R
quantile_pred.Rd

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())

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.

Examples

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

unclass(.pred_quantile)
#> [[1]]
#> [1]  0.5060559 -0.4771927 -0.1102855  0.1340882
#> 
#> [[2]]
#> [1] -0.5747400 -0.9983864 -0.5110095 -0.4906859
#> 
#> [[3]]
#> [1] -0.5466319 -0.7762539 -0.9111954 -0.4405479
#> 
#> [[4]]
#> [1] -0.56445200  0.06445882 -0.83717168  0.45958944
#> 
#> [[5]]
#> [1] -0.8900378  0.9594941  2.4158352 -0.6937202
#> 
#> 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,]  0.5060559 -0.47719270 -0.1102855  0.1340882
#> [2,] -0.5747400 -0.99838644 -0.5110095 -0.4906859
#> [3,] -0.5466319 -0.77625389 -0.9111954 -0.4405479
#> [4,] -0.5644520  0.06445882 -0.8371717  0.4595894
#> [5,] -0.8900378  0.95949406  2.4158352 -0.6937202

# Tidy format
library(tibble)
as_tibble(.pred_quantile)
#> # A tibble: 20 × 3
#>    .pred_quantile .quantile_levels  .row
#>             <dbl>            <dbl> <int>
#>  1         0.506               0.2     1
#>  2        -0.477               0.4     1
#>  3        -0.110               0.6     1
#>  4         0.134               0.8     1
#>  5        -0.575               0.2     2
#>  6        -0.998               0.4     2
#>  7        -0.511               0.6     2
#>  8        -0.491               0.8     2
#>  9        -0.547               0.2     3
#> 10        -0.776               0.4     3
#> 11        -0.911               0.6     3
#> 12        -0.441               0.8     3
#> 13        -0.564               0.2     4
#> 14         0.0645              0.4     4
#> 15        -0.837               0.6     4
#> 16         0.460               0.8     4
#> 17        -0.890               0.2     5
#> 18         0.959               0.4     5
#> 19         2.42                0.6     5
#> 20        -0.694               0.8     5