weibulltools (version 0.5.4)

plot_prob: Probability Plotting Method for Univariate Lifetime Distributions

Description

This function is used to apply the graphical technique of probability plotting.

Usage

plot_prob(x, y, event, id = rep("XXXXXX", length(x)),
  distribution = c("weibull", "lognormal", "loglogistic"),
  title_main = "Probability Plot", title_x = "Characteristic",
  title_y = "Unreliability", title_trace = "Sample")

Arguments

x

a numeric vector which consists of lifetime data. Lifetime data could be every characteristic influencing the reliability of a product, e.g. operating time (days/months in service), mileage (km, miles), load cycles.

y

a numeric vector which consists of estimated failure probabilities regarding the lifetime data in x.

event

a vector of binary data (0 or 1) indicating whether unit i is a right censored observation (= 0) or a failure (= 1).

id

a character vector for the identification of every unit.

distribution

supposed distribution of the random variable. Can be "weibull", "lognormal" or "loglogistic". Other distributions have not been implemented yet.

title_main

a character string which is assigned to the main title of the plot.

title_x

a character string which is assigned to the title of the x axis.

title_y

a character string which is assigned to the title of the y axis.

title_trace

a character string whis is assigned to the trace shown in the legend.

Value

Returns a plotly object containing the layout of the probability plot provided by plot_layout and the plotting positions.

Details

The marker label for x is determined by the first word provided in the argument title_x, i.e. if title_x = "Mileage in km" the x label of the marker is "Mileage".

The marker label for y is determined by the string provided in the argument title_y, i.e. if title_y = "Probability in percent" the y label of the marker is "Probability".

Examples

# NOT RUN {
obs   <- seq(10000, 100000, 10000)
state <- c(0, 1, 1, 0, 0, 0, 1, 0, 1, 0)
id <- LETTERS[1:length(obs)]

df_john <- johnson_method(x = obs, event = state, id = id)

plot_weibull <- plot_prob(x = df_john$characteristic,
                          y = df_john$prob,
                          event = df_john$status,
                          id = df_john$id,
                          distribution = "weibull",
                          title_main = "Weibull Analysis",
                          title_x = "Mileage in miles",
                          title_y = "Probability of Failure in %",
                          title_trace = "Failed Items")
# }