# plot_prob: Probability Plotting Method for Univariate Lifetime... In weibulltools: Statistical Methods for Life Data Analysis

## Description

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

## Usage

 ```1 2 3 4 5``` ```plot_prob(x, y, event, id = rep("XXXXXX", length(x)), distribution = c("weibull", "lognormal", "loglogistic", "normal", "logistic", "sev"), 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. The value can be `"weibull"`, `"lognormal"`, `"loglogistic"`, `"normal"`, `"logistic"` or `"sev"` (smallest extreme value). 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.

## 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".

## Value

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

## References

Meeker, William Q; Escobar, Luis A., Statistical methods for reliability data, New York: Wiley series in probability and statistics, 1998

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32``` ```# Alloy T7987 dataset taken from Meeker and Escobar(1998, p. 131) cycles <- c(300, 300, 300, 300, 300, 291, 274, 271, 269, 257, 256, 227, 226, 224, 213, 211, 205, 203, 197, 196, 190, 189, 188, 187, 184, 180, 180, 177, 176, 173, 172, 171, 170, 170, 169, 168, 168, 162, 159, 159, 159, 159, 152, 152, 149, 149, 144, 143, 141, 141, 140, 139, 139, 136, 135, 133, 131, 129, 123, 121, 121, 118, 117, 117, 114, 112, 108, 104, 99, 99, 96, 94) state <- c(rep(0, 5), rep(1, 67)) df_john <- johnson_method(x = cycles, event = state) # Example 1: Probability Plot Weibull: 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 = "Cycles", title_y = "Probability of Failure in %", title_trace = "Failed Items") # Example 2: Probability Plot Lognormal: plot_lognormal <- plot_prob(x = df_john\$characteristic, y = df_john\$prob, event = df_john\$status, id = df_john\$id, distribution = "lognormal", title_main = "Lognormal Analysis", title_x = "Cycles", title_y = "Probability of Failure in %", title_trace = "Failed Items") ```

weibulltools documentation built on May 2, 2019, 11:01 a.m.