% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/plotly_nhpp.R
\name{plotly_nhpp}
\alias{plotly_nhpp}
\title{Interactive NHPP Plot.}
\usage{
plotly_nhpp(
  nhpp_obj,
  showConf = TRUE,
  showGrid = TRUE,
  main = "NHPP Plot",
  xlab = "Cumulative Time",
  ylab = "Mean Cumulative Function",
  pointCol = "black",
  fitCol = "black",
  confCol = "black",
  gridCol = "lightgray",
  breakCol = "black",
  signif = 3,
  cols = NULL
)
}
\arguments{
\item{nhpp_obj}{An object of class 'nhpp', or a list of such objects. Each
object is created using the `nhpp()` 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 "NHPP Plot".}

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

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

\item{pointCol}{Color of the MCF data points. Default is "black". Used only
for a single nhpp object; ignored when `cols` is provided or multiple objects
are supplied.}

\item{fitCol}{Color of the model fit. Default is "black". Used only for a
single nhpp object; ignored when `cols` is provided or multiple objects are
supplied.}

\item{confCol}{Color of the confidence bounds. Default is "black". Used only
for a single nhpp object; ignored when `cols` is provided or multiple objects
are supplied.}

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

\item{breakCol}{Color of the breakpoints. Default is "black". Used only for a
single nhpp object; ignored when `cols` is provided or multiple objects are
supplied.}

\item{signif}{Significant digits of results. Default is 3. Must be a positive integer.}

\item{cols}{Optional character vector of colors, one per nhpp object. When
provided, each object's points, fit line, confidence bounds, and breakpoints
are all drawn in the corresponding color. Recycled if shorter than the number
of objects.}
}
\value{
A `plotly` object representing the interactive NHPP plot.
}
\description{
The function creates an interactive Non-Homogeneous Poisson Process (NHPP)
plot for one or more `nhpp` objects. When a list of objects is provided the
models are overlaid on the same plot, each rendered in a distinct color.
The plot shows the nonparametric Mean Cumulative Function (MCF) alongside
the parametric model fit and optional confidence bounds. Vertical lines
indicate change points if breakpoints are specified in the nhpp object.
}
\details{
The nonparametric MCF is overlaid with the fitted parametric Power Law
NHPP model, \eqn{E[N(t)] = \lambda t^\beta}. Use this plot to assess
whether the parametric model fits the observed event history and to
identify change points. Confidence bounds are based on the Fisher matrix
approximation of the fitted parameters. For piecewise models, vertical
dotted lines mark each breakpoint.
}
\examples{
library(ReliaGrowR)
times <- c(100, 200, 300, 400, 500)
events <- c(1, 2, 1, 3, 2)
fit <- nhpp(time = times, event = events)
plotly_nhpp(fit)

# Piecewise model with a breakpoint
times2 <- c(100, 200, 300, 400, 500, 600, 700, 800, 900, 1000)
events2 <- c(1, 2, 1, 1, 1, 2, 3, 1, 2, 4)
fit2 <- nhpp(time = times2, event = events2, breaks = 500, method = "LS")
plotly_nhpp(fit2, breakCol = "red")

# Overlay two models
plotly_nhpp(list(fit, fit2))
}
\seealso{
[plotly_mcf()] for the nonparametric MCF alone; [plotly_rga()] for
a Crow-AMSAA cumulative-failures view.
}
