Contains methods for examining bench test or field data using the well-known Weibull Analysis. It includes Monte Carlo simulation for estimating the life span of products that have not failed, taking account of registering and reporting delays as stated in (Verband der Automobilindustrie e.V. (VDA), 2016, <ISSN:0943-9412>). If the products looked upon are vehicles, the covered mileage can be estimated as well. It also provides non-parametric estimators like Median Ranks, Kaplan-Meier (Abernethy, 2006, <ISBN:978-0-9653062-3-2>), Johnson (Johnson, 1964, <ISBN:978-0444403223>), and Nelson-Aalen for failure probability estimation within samples that contain failures as well as censored data. Methods for estimating the parameters of lifetime distributions, like Maximum Likelihood and Median-Rank Regression, (Genschel and Meeker, 2010, <DOI:10.1080/08982112.2010.503447>) as well as the computation of confidence intervals of quantiles and probabilities using the delta method related to Fisher's confidence intervals (Meeker and Escobar, 1998, <ISBN:9780471673279>) and the beta-binomial confidence bounds are also included. If desired, the data can automatically be divided into subgroups using segmented regression. And if the number of subgroups in a Weibull Mixture Model is known, data can be analyzed using the EM-Algorithm. Besides the calculation, methods for interactive visualization of the edited data using *plotly* are provided as well. These visualizations include the layout of a probability plot for a specified distribution, the graphical technique of probability plotting and the possibility of adding regression lines and confidence bounds to existing plots.
|Author||Hensel Tim-Gunnar [aut, cre]|
|Maintainer||Hensel Tim-Gunnar <email@example.com>|
|Package repository||View on CRAN|
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