Takes a numeric vector and will return a vector that has been scaled by mean and standard deviation
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
This is set to 'auto' by default but can be a user supplied character string.
Details
Takes a numeric vector and will return a vector that has been scaled by mean and standard deviation.
The input vector must be numeric. The computation is fairly straightforward.
This may be helpful when trying to compare the distributions of data where a
distribution like beta from the fitdistrplus package which requires data to be
between 0 and 1
$$y[h] = (x - mean(x) / sd(x))$$
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_hyperbolic_augment(),
hai_polynomial_augment(),
hai_scale_zero_one_augment(),
hai_winsorized_move_augment(),
hai_winsorized_truncate_augment()
Other Scale:
hai_scale_zero_one_augment(),
hai_scale_zero_one_vec(),
hai_scale_zscore_vec(),
step_hai_scale_zscore()
Examples
df <- data.frame(x = mtcars$mpg)
hai_scale_zscore_augment(df, x)
#> # A tibble: 32 × 2
#> x hai_scale_zscore_x
#> <dbl> <dbl>
#> 1 21 0.151
#> 2 21 0.151
#> 3 22.8 0.450
#> 4 21.4 0.217
#> 5 18.7 -0.231
#> 6 18.1 -0.330
#> 7 14.3 -0.961
#> 8 24.4 0.715
#> 9 22.8 0.450
#> 10 19.2 -0.148
#> # ℹ 22 more rows