Interactive Duane Plot.

This function creates an interactive Duane plot for a duane object. The plot displays observed cumulative MTBF against cumulative test time on a log-log scale alongside the fitted Duane line and optional confidence bounds. Positive slope on the log-log scale indicates reliability growth.

Usage

plotly_duane(
  duane_obj,
  showConf = TRUE,
  showGrid = TRUE,
  main = "Duane Plot",
  xlab = "Cumulative Time",
  ylab = "Cumulative MTBF",
  pointCol = "black",
  fitCol = "black",
  confCol = "black",
  gridCol = "lightgray",
  signif = 3
)

Arguments

duane_obj

An object of class 'duane'. This object is created using the `duane` function from the ReliaGrowR package.

showConf

Show the confidence bounds (TRUE) or not (FALSE). Default is TRUE.

showGrid

Show grid (TRUE) or hide grid (FALSE). Default is TRUE.

main

Main title. Default is "Duane Plot".

xlab

X-axis label. Default is "Cumulative Time".

ylab

Y-axis label. Default is "Cumulative MTBF".

pointCol

Color of the point values. Default is "black".

fitCol

Color of the model fit. Default is "black".

confCol

Color of the confidence bounds. Default is "black".

gridCol

Color of the grid. Default is "lightgray".

signif

Significant digits of results. Default is 3. Must be a positive integer.

Value

A `plotly` object representing the interactive Duane plot.

Details

The Duane model fits a power-law relationship between cumulative MTBF and cumulative test time: \(\text{MTBF}_c = K \cdot T^\alpha\). On a log-log plot this appears as a straight line with slope \(\alpha\) (the growth rate) and intercept \(\log(K)\). A slope near 0 indicates no growth; a slope near 0.5 is typical for a managed development program.

See also

[plotly_rga()] for the Crow-AMSAA NHPP growth model on the same data.

Examples

library(ReliaGrowR)
times <- c(100, 200, 300, 400, 500)
failures <- c(1, 2, 1, 3, 2)
fit <- duane(times, failures)
plotly_duane(fit)