Generate quasi Anscombe data sets Type 5: Heteroskedasticity

Data sets Type 5 recreates the phenomenon of heteroskedasticity in the residuals.

Usage

sim_quasianscombe_set_5(df, fun = identity, residual_factor = 10)

Arguments

df

A data frame from sim_quasianscombe_set_1 (or similar).

fun

A function to apply to the index to multiply the residuals of the original model.

residual_factor

Numeric value to multiply residual to modify their variance.

Details

This function will take residuals $e_i$ and then get $e'_i = e_i * fun(i)$ and then rescale the $e'_i$ to the range of $e_i$.

Examples

df <- sim_quasianscombe_set_1()

dataset5 <- sim_quasianscombe_set_5(df)

dataset5
#> # A tibble: 500 × 2
#>        x     y
#>    <dbl> <dbl>
#>  1  1.25  3.61
#>  2  2.19  4.08
#>  3  2.40  4.20
#>  4  2.45  4.25
#>  5  2.57  4.25
#>  6  2.68  4.30
#>  7  2.70  4.32
#>  8  2.79  4.42
#>  9  2.97  4.60
#> 10  2.97  4.42
#> # … with 490 more rows

plot(dataset5)


plot(sim_quasianscombe_set_5(df, fun = rev))


plot(sim_quasianscombe_set_5(df, fun = sqrt))


plot(sim_quasianscombe_set_5(df, fun = log))


plot(sim_quasianscombe_set_5(df, fun = function(x) x^(1+0.6)))