The EnvStats functions listed below are useful for dealing with Type I censored data.
Data Transformations
Function Name  Description 
boxcoxCensored  Compute values of an objective for BoxCox 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
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 (logscale) 
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
Function Name  Description 
eqlnormCensored  Estimate quantiles of a Lognormal distribution (logscale) 
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:
There exists a function to estimate distribution parameters using censored data (see the section Estimating Distribution Parameters above).
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 leftcensored observations or below
all rightcensored observations. See the help file for eqnpar
for more information and
examples.
GoodnessofFit Tests
Function Name  Description 
gofTestCensored  Perform a goodnessoffit test based on Type I left or 
rightcensored data.  
print.gofCensored  Print an object of class "gofCensored" . 
plot.gofCensored  Plot an object of class "gofCensored" . 
Hypothesis Tests
Function Name  Description 
twoSampleLinearRankTestCensored  Perform twosample linear rank tests based on 
censored data.  
print.htestCensored  Printing method for object of class 
"htestCensored" . 

Plotting Probability Distributions
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 quantilequantile (QQ) plots, also called probability 
plots, based on Type I censored data.  
Prediction and Tolerance Intervals
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 (logscale) 
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:
There exists a function to estimate distribution parameters using censored data (see the section Estimating Distribution Parameters above).
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 leftcensored observations or below
all rightcensored observations. See the help files for predIntNpar
,
predIntNparSimultaneous
, and tolIntNpar
for more information and examples.
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