Global Weibull: Difference between revisions
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*'''[[WeibullBayesianResultsOption]]''' {{Template:APIComment|Available Bayesian-Weibull result options. This includes Median and Mean.}} | *'''[[WeibullBayesianResultsOption]]''' {{Template:APIComment|Available Bayesian-Weibull result options. This includes Median and Mean.}} | ||
*'''[[WeibullSolverCBMethod]]''' {{Template:APIComment|Available Weibull solver confidence bounds methods. This includes FisherMatrix, LikeihoodRatio, BetaBinomial, and KTO.}} | *'''[[WeibullSolverCBMethod]]''' {{Template:APIComment|Available Weibull solver confidence bounds methods. This includes FisherMatrix, LikeihoodRatio, BetaBinomial, and KTO.}} | ||
*'''[[WeibullSolverDistribution]]''' {{Template:APIComment|Available Weibull solver distributions. This includes Weibull, Normal, Exponential, Lognormal, G_Gamma, Logistic, Loglogistic, Gumbel, Gamma, and Bayesian-Weibull distribution.}} | *'''[[WeibullSolverDistribution]]''' {{Template:APIComment|Available Weibull solver distributions. This includes Weibull, Normal, Exponential, Lognormal, Generalized Gamma (G_Gamma), Logistic, Loglogistic, Gumbel, Gamma, and Bayesian-Weibull distribution.}} | ||
*'''[[WeibullSolverMethod]]''' {{Template:APIComment|Available Weibull solver analysis methods. This includes Rank Regression on X (RRX), Rank Regression on Y (RRY), and Maximum Likelihood Estimation (MLE).}} | *'''[[WeibullSolverMethod]]''' {{Template:APIComment|Available Weibull solver analysis methods. This includes Rank Regression on X (RRX), Rank Regression on Y (RRY), and Maximum Likelihood Estimation (MLE).}} | ||
*'''[[WeibullSolverNumParameters]]''' {{Template:APIComment|Available Weibull solver distribution parameters. This includes MS_1Parameter, MS_2Parameter, MS_3Parameter, and MS_Mixed.}} | *'''[[WeibullSolverNumParameters]]''' {{Template:APIComment|Available Weibull solver distribution parameters. This includes MS_1Parameter, MS_2Parameter, MS_3Parameter, and MS_Mixed.}} | ||
*'''[[WeibullSolverRankMethod]]''' {{Template:APIComment|Available Weibull solver ranking methods. This includes Median, kaplanMeir, and Actuarial. }} | *'''[[WeibullSolverRankMethod]]''' {{Template:APIComment|Available Weibull solver ranking methods. This includes Median, kaplanMeir, and Actuarial. }} | ||
Revision as of 18:12, 28 January 2014
This page lists all classes, methods and enumerations that are directly related to accessing the capabilities of a Weibull++ standard folio. The API functions related to plots that could be generated from either Weibull++ or ALTA standard folios can be found in WAPlots.
Classes and Methods
- WeibullAnalysisOptions Weibull solver analysis options
- WeibullAnalysisResults Describes various analysis results.
- WeibullBestFitOptions Whether each Weibull distribution is the best fit
- WeibullDataSet To instantiate a class in order to fit a Weibull model from your raw data.
- WeibullEvents Allows the user to create and display messages, questions, calculation progress, and more.
- WeibullGeneralOptions Weibull solver general options
Enumerations
- WeibullBayesianPriorDistribution Available Bayesian-Weibull distributions. This includes Normal, Lognormal, Exponential, and Uniform distributions.
- WeibullBayesianResultsOption Available Bayesian-Weibull result options. This includes Median and Mean.
- WeibullSolverCBMethod Available Weibull solver confidence bounds methods. This includes FisherMatrix, LikeihoodRatio, BetaBinomial, and KTO.
- WeibullSolverDistribution Available Weibull solver distributions. This includes Weibull, Normal, Exponential, Lognormal, Generalized Gamma (G_Gamma), Logistic, Loglogistic, Gumbel, Gamma, and Bayesian-Weibull distribution.
- WeibullSolverMethod Available Weibull solver analysis methods. This includes Rank Regression on X (RRX), Rank Regression on Y (RRY), and Maximum Likelihood Estimation (MLE).
- WeibullSolverNumParameters Available Weibull solver distribution parameters. This includes MS_1Parameter, MS_2Parameter, MS_3Parameter, and MS_Mixed.
- WeibullSolverRankMethod Available Weibull solver ranking methods. This includes Median, kaplanMeir, and Actuarial.