FcnsByCatCensoredData: EnvStats Functions for Censored Data

Description

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

Arguments

Details

Data Transformations

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

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

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:

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 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 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

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

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

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:

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 left-censored observations or below all right-censored observations. See the help files for predIntNpar, predIntNparSimultaneous, and tolIntNpar for more information and examples.