Statistical Methods for Life Data Analysis
Computation of Johnson Ranks
Beta Binomial Confidence Bounds for Quantiles and Probabilities
Beta Binomial Confidence Bounds for Quantiles and Probabilities
Fisher's Confidence Bounds for Quantiles and Probabilities
Fisher's Confidence Bounds for Quantiles and Probabilities
Delta Method for Parametric Lifetime Distributions
Parameter Estimation of a Delay Distribution
Parameter Estimation of a Delay Distribution
Parameter Estimation of the Delay in Registration Distribution
Parameter Estimation of the Delay in Report Distribution
Parameter Estimation of an Annual Mileage Distribution
Parameter Estimation of an Annual Mileage Distribution
Estimation of Failure Probabilities
Estimation of Failure Probabilities
Estimation of Failure Probabilities using Johnson's Method
Estimation of Failure Probabilities using the Kaplan-Meier Estimator
Log-Likelihood Function for Parametric Lifetime Distributions
Log-Likelihood Function for Parametric Lifetime Distributions
Log-Likelihood Profile Function for Parametric Lifetime Distributions ...
Log-Likelihood Profile Function for Parametric Lifetime Distributions ...
Adjustment of Operating Times by Delays using a Monte Carlo Approach
Adjustment of Operating Times by Delays using a Monte Carlo Approach
MCS Delay Data
Adjustment of Operating Times by Delays in Registration using a Monte ...
Adjustment of Operating Times by Delays in Report using a Monte Carlo ...
Adjustment of Operating Times by Delays using a Monte Carlo Approach
Simulation of Unknown Covered Distances using a Monte Carlo Approach
Simulation of Unknown Covered Distances using a Monte Carlo Approach
MCS Mileage Data
Weibull Mixture Model Estimation using EM-Algorithm
Weibull Mixture Model Estimation using EM-Algorithm
Mixture Model Identification using Segmented Regression
Mixture Model Identification using Segmented Regression
EM-Algorithm using Newton-Raphson Method
ML Estimation for Parametric Lifetime Distributions
ML Estimation for Parametric Lifetime Distributions
Estimation of Failure Probabilities using Median Ranks
Estimation of Failure Probabilities using the Nelson-Aalen Estimator
Add Confidence Region(s) for Quantiles and Probabilities
Add Confidence Region(s) for Quantiles and Probabilities
Layout of the Probability Plot
Add Estimated Population Line to a Probability Plot
Add Estimated Population Line(s) to a Probability Plot
Add Estimated Population Lines of a Separated Mixture Model to a Proba...
Add Population Line(s) to an Existing Grid
Probability Plotting Method for Univariate Lifetime Distributions
Probability Plotting Method for Univariate Lifetime Distributions
Probability Plot for Separated Mixture Models
Prediction of Failure Probabilities for Parametric Lifetime Distributi...
Prediction of Quantiles for Parametric Lifetime Distributions
R-Squared-Profile Function for Parametric Lifetime Distributions with ...
R-Squared-Profile Function for Parametric Lifetime Distributions with ...
Rank Regression for Parametric Lifetime Distributions
Rank Regression for Parametric Lifetime Distributions
Reliability Data
weibulltools
Provides statistical methods and visualizations that are often used in reliability engineering. Comprises a compact and easily accessible set of methods and visualization tools that make the examination and adjustment as well as the analysis and interpretation of field data (and bench tests) as simple as possible. 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 are included. The package supports methods like Maximum Likelihood and Rank Regression, (Genschel and Meeker, 2010, <DOI:10.1080/08982112.2010.503447>) for the estimation of multiple parametric lifetime distributions, 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. If desired, mixture model analysis can be done with segmented regression and the EM algorithm. Besides the well-known Weibull analysis, the package also contains Monte Carlo methods for the correction and completion of imprecisely recorded or unknown lifetime characteristics. (Verband der Automobilindustrie e.V. (VDA), 2016, <ISSN:0943-9412>). Plots are created statically ('ggplot2') or interactively ('plotly') and can be customized with functions of the respective visualization package. The graphical technique of probability plotting as well as the addition of regression lines and confidence bounds to existing plots are supported.
Useful links