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Augment Function Hyperbolic

Source: R/augment-hai-hyperbolic.R
hai_hyperbolic_augment.Rd

Takes a numeric vector(s) or date and will return a tibble of one of the following:

  • "sin"

  • "cos"

  • "tan"

  • "sincos"

  • c("sin","cos","tan", "sincos")

Usage

hai_hyperbolic_augment(
  .data,
  .value,
  .names = "auto",
  .scale_type = c("sin", "cos", "tan", "sincos")
)

Arguments

.data

The data being passed that will be augmented by the function.

.value

This is passed rlang::enquo() to capture the vectors you want to augment.

.names

The default is "auto"

.scale_type

A character of one of the following: "sin","cos","tan", "sincos" All can be passed by setting the param equal to c("sin","cos","tan","sincos")

Value

A augmented tibble

Details

Takes a numeric vector or date and will return a vector of one of the following:

  • "sin"

  • "cos"

  • "tan"

  • "sincos"

  • c("sin","cos","tan", "sincos")

This function is intended to be used on its own in order to add columns to a tibble.

See also

Other Augment Function: hai_fourier_augment(), hai_fourier_discrete_augment(), hai_polynomial_augment(), hai_scale_zero_one_augment(), hai_scale_zscore_augment(), hai_winsorized_move_augment(), hai_winsorized_truncate_augment()

Author

Steven P. Sanderson II, MPH

Examples

suppressPackageStartupMessages(library(dplyr))

len_out <- 10
by_unit <- "month"
start_date <- as.Date("2021-01-01")

data_tbl <- tibble(
  date_col = seq.Date(from = start_date, length.out = len_out, by = by_unit),
  a = rnorm(len_out),
  b = runif(len_out)
)

hai_hyperbolic_augment(data_tbl, b, .scale_type = "sin")
#> # A tibble: 10 × 4
#>    date_col        a      b hyperbolic_b_sin
#>    <date>      <dbl>  <dbl>            <dbl>
#>  1 2021-01-01 -0.156 0.660            0.613 
#>  2 2021-02-01 -1.27  0.0942           0.0941
#>  3 2021-03-01 -0.270 0.0682           0.0681
#>  4 2021-04-01 -0.389 0.134            0.133 
#>  5 2021-05-01 -1.11  0.378            0.369 
#>  6 2021-06-01 -0.658 0.522            0.499 
#>  7 2021-07-01  3.24  0.0510           0.0510
#>  8 2021-08-01 -0.180 0.194            0.193 
#>  9 2021-09-01 -0.176 0.396            0.385 
#> 10 2021-10-01  0.378 0.824            0.734 
hai_hyperbolic_augment(data_tbl, b, .scale_type = "tan")
#> # A tibble: 10 × 4
#>    date_col        a      b hyperbolic_b_tan
#>    <date>      <dbl>  <dbl>            <dbl>
#>  1 2021-01-01 -0.156 0.660            0.776 
#>  2 2021-02-01 -1.27  0.0942           0.0945
#>  3 2021-03-01 -0.270 0.0682           0.0683
#>  4 2021-04-01 -0.389 0.134            0.134 
#>  5 2021-05-01 -1.11  0.378            0.397 
#>  6 2021-06-01 -0.658 0.522            0.575 
#>  7 2021-07-01  3.24  0.0510           0.0511
#>  8 2021-08-01 -0.180 0.194            0.197 
#>  9 2021-09-01 -0.176 0.396            0.418 
#> 10 2021-10-01  0.378 0.824            1.08