Learning modules for reliability analysis including modules for Reliability,
  Availability, and Maintainability (RAM) Analysis, Life Data Analysis, Reliability Testing,
  Repairable Systems Analysis, and Reliability Block Diagrams.

Build interactive Reliability Probability Plots with 'plotly' by Carson Sievert (2020) <https://plotly.com/r/>, an interactive web-based graphing library.

Provides a comprehensive suite of utilities for univariate continuous probability distributions and reliability models. Includes functions to compute the probability density, cumulative distribution, quantile, reliability, and hazard functions, along with random variate generation. Also offers diagnostic and model assessment tools  such as Quantile-Quantile (Q-Q) and Probability-Probability (P-P) plots, the Kolmogorov-Smirnov goodness-of-fit test, and model selection criteria including the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Currently implements the following distributions: Burr X, Chen, Exponential Extension, Exponentiated Logistic, Exponentiated Weibull, Exponential Power, Flexible Weibull, Generalized Exponential, Gompertz, Generalized Power Weibull, Gumbel, Inverse Generalized Exponential, Linear Failure Rate, Log-Gamma, Logistic-Exponential, Logistic-Rayleigh, Log-log, Marshall-Olkin Extended Exponential, Marshall-Olkin Extended Weibull, and Weibull Extension distributions. Serves as a valuable resource for teaching and research in probability theory, reliability analysis, and applied statistical modeling.

An interactive web application for reliability analysis using the 'shiny' <https://shiny.posit.co/> framework. The app provides an easy-to-use interface for performing reliability analysis using 'WeibullR' <https://cran.r-project.org/package=WeibullR> and 'ReliaGrowR' <https://cran.r-project.org/package=ReliaGrowR>.

Functions to facilitate inference on the relative importance of predictors in a linear or generalized linear model, and a couple of useful Tcl/Tk widgets.