% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plotly_duane.R
\name{plotly_duane}
\alias{plotly_duane}
\title{Interactive Duane Plot.}
\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{
\item{duane_obj}{An object of class 'duane'. This object is created
using the `duane` function from the ReliaGrowR package.}

\item{showConf}{Show the confidence bounds (TRUE) or not (FALSE). Default is TRUE.}

\item{showGrid}{Show grid (TRUE) or hide grid (FALSE). Default is TRUE.}

\item{main}{Main title. Default is "Duane Plot".}

\item{xlab}{X-axis label. Default is "Cumulative Time".}

\item{ylab}{Y-axis label. Default is "Cumulative MTBF".}

\item{pointCol}{Color of the point values. Default is "black".}

\item{fitCol}{Color of the model fit. Default is "black".}

\item{confCol}{Color of the confidence bounds. Default is "black".}

\item{gridCol}{Color of the grid. Default is "lightgray".}

\item{signif}{Significant digits of results. Default is 3. Must be a positive integer.}
}
\value{
A `plotly` object representing the interactive Duane plot.
}
\description{
This function creates an interactive Duane plot for a \code{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.
}
\details{
The Duane model fits a power-law relationship between cumulative MTBF and
cumulative test time: \eqn{\text{MTBF}_c = K \cdot T^\alpha}. On a
log-log plot this appears as a straight line with slope \eqn{\alpha} (the
growth rate) and intercept \eqn{\log(K)}. A slope near 0 indicates no
growth; a slope near 0.5 is typical for a managed development program.
}
\examples{
library(ReliaGrowR)
times <- c(100, 200, 300, 400, 500)
failures <- c(1, 2, 1, 3, 2)
fit <- duane(times, failures)
plotly_duane(fit)
}
\seealso{
[plotly_rga()] for the Crow-AMSAA NHPP growth model on the same data.
}
