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

Details

Data Transformations

Function NameDescription
boxcoxCensoredCompute values of an objective for Box-Cox Power
transformations, or compute optimal transformation,
for Type I censored data.
print.boxcoxCensoredPrint an object of class "boxcoxCensored".
plot.boxcoxCensoredPlot an object of class "boxcoxCensored".

Estimating Distribution Parameters

Function NameDescription
egammaCensoredEstimate shape and scale parameters for a gamma distribution
based on Type I censored data.
egammaAltCensoredEstimate mean and CV for a gamma distribution
based on Type I censored data.
elnormCensoredEstimate parameters for a lognormal distribution (log-scale)
based on Type I censored data.
elnormAltCensoredEstimate parameters for a lognormal distribution (original scale)
based on Type I censored data.
enormCensoredEstimate parameters for a Normal distribution based on Type I
censored data.
epoisCensoredEstimate parameter for a Poisson distribution based on Type I
censored data.
enparCensoredEstimate the mean and standard deviation nonparametrically.
gpqCiNormSinglyCensoredGenerate the generalized pivotal quantity used to construct a
confidence interval for the mean of a Normal distribution based
on Type I singly censored data.
gpqCiNormMultiplyCensoredGenerate 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.estimateCensoredPrint an object of class "estimateCensored".

Estimating Distribution Quantiles

Function NameDescription
eqlnormCensoredEstimate quantiles of a Lognormal distribution (log-scale)
based on Type I censored data, and optionally construct
a confidence interval for a quantile.
eqnormCensoredEstimate 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 section Estimating Distribution Parameters above).

  2. There exists a function to estimate quantiles for that distribution based on complete data (see the help file Estimating 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

Function NameDescription
gofTestCensoredPerform a goodness-of-fit test based on Type I left- or
right-censored data.
print.gofCensoredPrint an object of class "gofCensored".
plot.gofCensoredPlot an object of class "gofCensored".

Hypothesis Tests

Function NameDescription
twoSampleLinearRankTestCensoredPerform two-sample linear rank tests based on
censored data.
print.htestCensoredPrinting method for object of class
"htestCensored".

Plotting Probability Distributions

Function NameDescription
cdfCompareCensoredPlot two cumulative distribution functions based on Type I
censored data.
ecdfPlotCensoredPlot an empirical cumulative distribution function based on
Type I censored data.
ppointsCensoredCompute plotting positions for Type I censored data.
qqPlotCensoredProduce quantile-quantile (Q-Q) plots, also called probability
plots, based on Type I censored data.

Prediction and Tolerance Intervals

Function NameDescription
gpqTolIntNormSinglyCensoredGenerate the generalized pivotal quantity used to construct a
tolerance interval for a Normal distribution based
on Type I singly censored data.
gpqTolIntNormMultiplyCensoredGenerate the generalized pivotal quantity used to construct a
tolerance interval for a Normal distribution based
on Type I multiply censored data.
tolIntLnormCensoredTolerance interval for a lognormal distribution (log-scale)
based on Type I censored data.
tolIntNormCensoredTolerance 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 section Estimating Distribution Parameters above).

  2. There exists a function to create a prediction or tolerance interval for that distribution based on complete data (see the help files Prediction Intervals and Tolerance 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.