Type:	Package
Title:	Interactive Weibull Probability Plots
Version:	0.3.2
Description:	Build interactive Weibull Probability Plots with 'WeibullR' by David Silkworth and Jurgen Symynck (2022) https://CRAN.R-project.org/package=WeibullR, an R package for Weibull analysis, and 'plotly' by Carson Sievert (2020) https://plotly-r.com, an interactive web-based graphing library.
URL:	https://paulgovan.github.io/WeibullR.plotly/, https://github.com/paulgovan/WeibullR.plotly
BugReports:	https://github.com/paulgovan/WeibullR.plotly/issues
License:	Apache License version 1.1 | Apache License version 2.0 [expanded from: Apache License]
Imports:	plotly, ReliaGrowR, WeibullR
Suggests:	knitr, rmarkdown, spelling, testthat (≥ 3.0.0), WeibullR.learnr, WeibullR.shiny
Encoding:	UTF-8
RoxygenNote:	7.3.3
Config/testthat/edition:	3
Language:	en-US
NeedsCompilation:	no
Packaged:	2025-09-24 02:28:37 UTC; paulgovan
Author:	Paul Govan [aut, cre, cph]
Maintainer:	Paul Govan <paul.govan2@gmail.com>
Repository:	CRAN
Date/Publication:	2025-09-24 05:11:18 UTC

WeibullR.plotly: Interactive Weibull Probability Plots

Description

Build interactive Weibull Probability Plots with 'WeibullR' by David Silkworth and Jurgen Symynck (2022) https://CRAN.R-project.org/package=WeibullR, an R package for Weibull analysis, and 'plotly' by Carson Sievert (2020) https://plotly-r.com, an interactive web-based graphing library.

Author(s)

Maintainer: Paul Govan paul.govan2@gmail.com (ORCID) [copyright holder]

See Also

Useful links:

• https://paulgovan.github.io/WeibullR.plotly/

• https://github.com/paulgovan/WeibullR.plotly

• Report bugs at https://github.com/paulgovan/WeibullR.plotly/issues

Interactive Contour Plot

Description

This function creates an interactive contour plot for one or more 'wblr' objects, each assumed to have confidence contours generated via ‘method.conf = ’lrb''. The function overlays all contours in a single plot and displays their respective MLE point estimates.

Usage

plotly_contour(
  wblr_obj,
  main = "Contour Plot",
  xlab = "Eta",
  ylab = "Beta",
  showGrid = TRUE,
  cols = NULL,
  gridCol = "lightgray",
  signif = 3
)

Arguments

Value

A 'plotly' object representing the interactive contour plot.

Examples

library(WeibullR)
library(WeibullR.plotly)

failures1 <- c(30, 49, 82, 90, 96)
failures2 <- c(20, 40, 60, 80, 100)
obj1 <- wblr.conf(wblr.fit(wblr(failures1), method.fit = 'mle'), method.conf = 'lrb')
obj2 <- wblr.conf(wblr.fit(wblr(failures2), method.fit = 'mle'), method.conf = 'lrb')
plotly_contour(list(obj1, obj2), main = "Overlayed Contours")

Interactive Duane Plot.

Description

This function creates an interactive Duane plot for a duane object. The plot includes options to customize the appearance, such as colors and grid visibility.

Usage

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

Arguments

Value

The function returns no value. It generates an interactive Duane plot.

Examples

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

Interactive Reliability Growth Plot.

Description

The function creates an interactive reliability growth plot for an 'rga' object. The plot includes cumulative failures over time, the model fit, and optional confidence bounds. Vertical lines indicate change points if breakpoints are specified in the rga object.

Usage

plotly_rga(
  rga_obj,
  showConf = TRUE,
  showGrid = TRUE,
  main = "Reliability Growth Plot",
  xlab = "Cumulative Time",
  ylab = "Cumulative Failures",
  pointCol = "black",
  fitCol = "black",
  confCol = "black",
  gridCol = "lightgray",
  breakCol = "black"
)

Arguments

Value

The function returns no value. It generates an interactive plotly plot.

Examples

library(ReliaGrowR)
times<-c(100, 200, 300, 400, 500)
failures<-c(1, 2, 1, 3, 2)
rga<-rga(times, failures)
plotly_rga(rga)

times <- c(100, 200, 300, 400, 500, 600, 700, 800, 900, 1000)
failures <- c(1, 2, 1, 1, 1, 2, 3, 1, 2, 4)
breakpoints <- 400
rga2 <- rga(times, failures, model_type = "Piecewise NHPP", breaks = breakpoints)
plotly_rga(rga2, fitCol = "blue", confCol = "blue", breakCol = "red")

Interactive Probability Plot.

Description

This function creates an interactive probability plot for a wblr object. It can include confidence bounds, suspension data, and a results table.

Usage

plotly_wblr(
  wblr_obj,
  susp = NULL,
  showConf = TRUE,
  showSusp = TRUE,
  showRes = TRUE,
  showGrid = TRUE,
  main = "Probability Plot",
  xlab = "Time to Failure",
  ylab = "Probability",
  probCol = "black",
  fitCol = "black",
  confCol = "black",
  intCol = "black",
  gridCol = "lightgray",
  signif = 3
)

Arguments

Value

The function returns no value. It creates an interactive probability plot.

Examples

library(WeibullR)
library(WeibullR.plotly)
failures<-c(30, 49, 82, 90, 96)
obj<-wblr.conf(wblr.fit(wblr(failures)))
plotly_wblr(obj)

suspensions<-c(100, 45, 10)
obj<-wblr.conf(wblr.fit(wblr(failures, suspensions)))
plotly_wblr(obj, suspensions, fitCol = 'blue', confCol
= 'blue')
inspection_data <- data.frame(left=c(0, 6.12, 19.92, 29.64, 35.4, 39.72, 45.32, 52.32),
                           right=c(6.12, 19.92, 29.64, 35.4, 39.72, 45.32, 52.32, 63.48),
                           qty=c(5, 16, 12, 18, 18, 2, 6, 17))
suspensions <- data.frame(time = 63.48, event = 0, qty = 73)
obj <- wblr(suspensions, interval = inspection_data)
obj <- wblr.fit(obj, method.fit = "mle")
obj <- wblr.conf(obj, method.conf = "fm", lty = 2)
suspensions <- as.vector(suspensions$time)
plotly_wblr(obj, susp = suspensions, fitCol = 'red', confCol = 'red', intCol = 'blue',
        main = 'Parts Cracking Inspection Interval Analysis',
        ylab =  'Cumulative % Cracked', xlab='Inspection Time')
failures <- c(25, 30, 42, 49, 55, 67, 73, 82, 90, 96, 101, 110, 120, 132, 145)
fit <- wblr.conf(wblr.fit(wblr(failures), dist = "weibull3p"))
plotly_wblr(fit, fitCol='darkgreen', confCol = 'darkgreen')