weibulltools (version 2.1.0)

plot_mod_mix: 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",
  ...
)

Value

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

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".

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"
)