Confidence Intervals

Modeling and simulation (M&S) validation for operational testing often involves comparing live data with simulation outputs. Statistical methods known as functional data analysis (FDA) provides techniques for analyzing large data sets (“large” meaning that a single trial has a lot of information associated with it), such as radar tracks. We preview how FDA methods could assist M&S validation by providing statistical tools handling these large data sets. This may facilitate analyses that make use of more of the data available and thus allows for better detection of differences between M&S predictions and live test results....

This tutorial demonstrates how to plot reliability functions parametrically in R using the output from any reliability modeling software. It provides code and sample plots of reliability and failure rate functions with confidence intervals for three different skewed probability distributions the exponential, the two-parameter Weibull, and the lognormal. These three distributions are the most common parametric models for reliability or survival analysis. This paper also provides mathematical background for the models and recommendations for when to use them....