plot_mod_mix: Add Estimated Population Lines of a Separated Mixture Model...
In weibulltools: Statistical Methods for Life Data Analysis

plot_mod_mix

R Documentation

Add Estimated Population Lines of a Separated Mixture Model to a Probability Plot

Description

plot_mod_mix() is no longer under active development, switching to plot_mod is recommended.

Usage

plot_mod_mix(
  p_obj,
  x,
  status,
  mix_output,
  distribution = c("weibull", "lognormal", "loglogistic"),
  title_trace = "Fit",
  ...
)

Arguments

`p_obj`	A plot object returned by plot_prob_mix.
`x`	A numeric vector containing the x-coordinates of the respective regression line.
`status`	A vector of binary data (0 or 1) indicating whether a unit is a right censored observation (= 0) or a failure (= 1).
`mix_output`	A list returned by mixmod_regression or mixmod_em, which consists of elements necessary to visualize the regression lines.
`distribution`	Supposed distribution of the random variable.
`title_trace`	A character string which is assigned to the legend trace.
`...`	Further arguments passed to or from other methods. Currently not used.

Details

This function adds one or multiple estimated regression lines to an existing probability plot plot_prob). Depending on the output of the function mixmod_regression or mixmod_em one or multiple lines are plotted.

The name of the legend entry is a combination of the title_trace and the number of determined subgroups. If title_trace = "Line" and the data has been split in two groups, the legend entries would be "Line: 1" and "Line: 2".

Value

A plot object containing the probability plot with plotting positions and estimated regression line(s).

References

Doganaksoy, N.; Hahn, G.; Meeker, W. Q., Reliability Analysis by Failure Mode, Quality Progress, 35(6), 47-52, 2002

Examples

# Vectors:
hours <- voltage$hours
status <- voltage$status

# Example 1 - Using result of mixmod_em in mix_output:
mix_mod_em <- mixmod_em(
  x = hours,
  status = status,
  distribution = "weibull",
  conf_level = 0.95,
  k = 2,
  method = "EM",
  n_iter = 150
)

plot_weibull_em <- plot_prob_mix(
  x = hours,
  status = status,
  id = id,
  distribution = "weibull",
  mix_output = mix_mod_em
)

plot_weibull_emlines <- plot_mod_mix(
  p_obj = plot_weibull_em,
  x = hours,
  status = status,
  mix_output = mix_mod_em,
  distribution = "weibull"
)

# Example 2 - Using result of mixmod_regression in mix_output:
john <- johnson_method(x = hours, status = status)
mix_mod_reg <- mixmod_regression(
  x = john$x,
  y = john$prob,
  status = john$status,
  distribution = "weibull"
)

plot_weibull_reg <- plot_prob_mix(
  x = john$x,
  status = john$status,
  id = john$id,
  distribution = "weibull",
  mix_output = mix_mod_reg,
)

plot_weibull_reglines <- plot_mod_mix(
  p_obj = plot_weibull_reg,
  x = john$x,
  status = john$status,
  mix_output = mix_mod_reg,
  distribution = "weibull"
)

weibulltools documentation built on April 5, 2023, 5:10 p.m.