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EnvStats (version 2.1.0)

FcnsByCatCensoredData: EnvStats Functions for Censored Data

Description

The EnvStats functions listed below are useful for dealing with Type I censored data.

Arguments

concept

Less Than Detection Limit

Details

Data Transformations ll{ Function Name Description boxcoxCensored Compute values of an objective for Box-Cox Power transformations, or compute optimal transformation, for Type I censored data. print.boxcoxCensored Print an object of class "boxcoxCensored". plot.boxcoxCensored Plot an object of class "boxcoxCensored". } Estimating Distribution Parameters ll{ Function Name Description egammaCensored Estimate shape and scale parameters for a gamma distribution based on Type I censored data. egammaAltCensored Estimate mean and CV for a gamma distribution based on Type I censored data. elnormCensored Estimate parameters for a lognormal distribution (log-scale) based on Type I censored data. elnormAltCensored Estimate parameters for a lognormal distribution (original scale) based on Type I censored data. enormCensored Estimate parameters for a Normal distribution based on Type I censored data. epoisCensored Estimate parameter for a Poisson distribution based on Type I censored data. enparCensored Estimate the mean and standard deviation nonparametrically. gpqCiNormSinglyCensored Generate the generalized pivotal quantity used to construct a confidence interval for the mean of a Normal distribution based on Type I singly censored data. gpqCiNormMultiplyCensored Generate the generalized pivotal quantity used to construct a confidence interval for the mean of a Normal distribution based on Type I multiply censored data. print.estimateCensored Print an object of class "estimateCensored". } Estimating Distribution Quantiles ll{ Function Name Description eqlnormCensored Estimate quantiles of a Lognormal distribution (log-scale) based on Type I censored data, and optionally construct a confidence interval for a quantile. eqnormCensored Estimate quantiles of a Normal distribution based on Type I censored data, and optionally construct a confidence interval for a quantile. } All of the functions for computing quantiles (and associated confidence intervals) for complete (uncensored) data are listed in the help file Estimating Distribution Quantiles. All of these functions, with the exception of eqnpar, will accept an object of class "estimateCensored". Thus, you may estimate quantiles (and construct approximate confidence intervals) for any distribution for which:
  1. There exists a function to estimate distribution parameters using censored data (see the sectionEstimating Distribution Parametersabove).
  2. There exists a function to estimate quantiles for that distribution based on complete data (see the help fileEstimating Distribution Quantiles).
Nonparametric estimates of quantiles (and associated confidence intervals) can be constructed from censored data as long as the order statistics used in the results are above all left-censored observations or below all right-censored observations. See the help file for eqnpar for more information and examples. Goodness-of-Fit Tests ll{ Function Name Description gofTestCensored Perform a goodness-of-fit test based on Type I left- or right-censored data. print.gofCensored Print an object of class "gofCensored". plot.gofCensored Plot an object of class "gofCensored". } Hypothesis Tests ll{ Function Name Description twoSampleLinearRankTestCensored Perform two-sample linear rank tests based on censored data. print.htestCensored Printing method for object of class "htestCensored". } Plotting Probability Distributions ll{ Function Name Description cdfCompareCensored Plot two cumulative distribution functions based on Type I censored data. ecdfPlotCensored Plot an empirical cumulative distribution function based on Type I censored data. ppointsCensored Compute plotting positions for Type I censored data. qqPlotCensored Produce quantile-quantile (Q-Q) plots, also called probability plots, based on Type I censored data. } Prediction and Tolerance Intervals ll{ Function Name Description gpqTolIntNormSinglyCensored Generate the generalized pivotal quantity used to construct a tolerance interval for a Normal distribution based on Type I singly censored data. gpqTolIntNormMultiplyCensored Generate the generalized pivotal quantity used to construct a tolerance interval for a Normal distribution based on Type I multiply censored data. tolIntLnormCensored Tolerance interval for a lognormal distribution (log-scale) based on Type I censored data. tolIntNormCensored Tolerance interval for a Normal distribution based on Type I censored data. } All of the functions for computing prediction and tolerance intervals for complete (uncensored) data are listed in the help files Prediction Intervals and Tolerance Intervals. All of these functions, with the exceptions of predIntNpar and tolIntNpar, will accept an object of class "estimateCensored". Thus, you may construct approximate prediction or tolerance intervals for any distribution for which:
  1. There exists a function to estimate distribution parameters using censored data (see the sectionEstimating Distribution Parametersabove).
  2. There exists a function to create a prediction or tolerance interval for that distribution based on complete data (see the help filesPrediction IntervalsandTolerance Intervals).
Nonparametric prediction and tolerance intervals can be constructed from censored data as long as the order statistics used in the results are above all left-censored observations or below all right-censored observations. See the help files for predIntNpar, predIntNparSimultaneous, and tolIntNpar for more information and examples.