It implements the subjectively censored Weibull MLE and censored Weibull mixture methods for the lower quantile estimation. Quantile estimates from these two methods are robust to model misspecification in the lower tail. It also includes functions to evaluation the standard error of the resulting quantile estimates. Also, the methods here can be used to fit the Weibull or Weibull mixture for the Type-I or Type-II right censored data.
|Author||Yang (Seagle) Liu|
|Date of publication||2014-12-04 01:14:47|
|Maintainer||Yang (Seagle) Liu <email@example.com>|
|License||GPL (>= 2)|
bootstrapCenWbMix: Bootstrap Censored Weibull Mixture for censoring threshold...
bootstrapCMLE: Bootstrap Censored Weibull MLE for censoring threshold...
cenWbMLE.T1: censored Weibull MLE for Type I right-censored data
cenWbMLE.T2: censored Weibull MLE for Type II right-censored data
emCenWbMix.T1: EM algorithm for the Type-I right censored Weibull Mixture...
emCenWbMix.T2: EM algorithm for the Type-II right censored Weibull Mixture...
quanWbMix: Calculate the quantiles of a mixture of two Weibull...
simWbMix: Simulate data from a mixture of two Weibull distributions
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.