Compare Mills Ratio and Hazard Function

Usage

compare_mills_hazard(x, distribution = "normal", ...)

Arguments

x: Numeric vector of values
distribution: Character string specifying distribution
...: Additional distribution parameters

Value

Data frame with x, mills_ratio, and hazard columns

Examples

# Compare for normal distribution
compare_mills_hazard(seq(0, 5, by = 0.5), "normal")
#>      x mills_ratio    hazard distribution
#> 1  0.0   1.2533141 0.7978846       normal
#> 2  0.5   0.8763645 1.1410778       normal
#> 3  1.0   0.6556795 1.5251353       normal
#> 4  1.5   0.5158156 1.9386772       normal
#> 5  2.0   0.4213692 2.3732155       normal
#> 6  2.5   0.3542651 2.8227448       normal
#> 7  3.0   0.3045903 3.2830987       normal
#> 8  3.5   0.2665678 3.7513913       normal
#> 9  4.0   0.2366524 4.2256071       normal
#> 10 4.5   0.2125706 4.7043198       normal
#> 11 5.0   0.1928081 5.1865040       normal

# Tidyverse visualization
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
library(ggplot2)
compare_mills_hazard(seq(0.1, 5, by = 0.1), "normal") %>%
  tidyr::pivot_longer(c(mills_ratio, hazard),
                       names_to = "function_type",
                       values_to = "value") %>%
  ggplot(aes(x, value, color = function_type)) +
  geom_line() +
  scale_y_log10() +
  labs(title = "Mills Ratio vs Hazard Function",
       subtitle = "Note: h(x) = 1/m(x)")