gofCensored.object {EnvStats}

S3 Class "gofCensored"

Description

Objects of S3 class "gofCensored" are returned by the EnvStats function gofTestCensored.

Details

Objects of S3 class "gofCensored" are lists that contain information about the assumed distribution, the amount of censoring, the estimated or user-supplied distribution parameters, and the test statistic and p-value.

Value

Required Components
The following components must be included in a legitimate list of class "gofCensored".

distribution

a character string indicating the name of the assumed distribution (see
Distribution.df).

dist.abb

a character string containing the abbreviated name of the distribution (see
Distribution.df).

distribution.parameters

a numeric vector with a names attribute containing the names and values of the estimated or user-supplied distribution parameters associated with the assumed distribution.

n.param.est

a scalar indicating the number of distribution parameters estimated prior to performing the goodness-of-fit test. The value of this component will be 0 if the parameters were supplied by the user.

estimation.method

a character string indicating the method used to compute the estimated parameters. The value of this component will depend on the available estimation methods (see Distribution.df). The value of this component will be NULL if the parameters were supplied by the user.

statistic

a numeric scalar with a names attribute containing the name and value of the goodness-of-fit statistic.

sample.size

a numeric scalar containing the number of non-missing observations in the sample used for the goodness-of-fit test.

censoring.side

character string indicating whether the data are left- or right-censored.

censoring.levels

numeric scalar or vector indicating the censoring level(s).

percent.censored

numeric scalar indicating the percent of non-missing observations that are censored.

parameters

numeric vector with a names attribute containing the name(s) and value(s) of the parameter(s) associated with the test statistic given in the statistic component.

z.value

(except when test="chisq" or test="ks") numeric scalar containing the z-value associated with the goodness-of-fit statistic.

p.value

numeric scalar containing the p-value associated with the goodness-of-fit statistic.

alternative

character string indicating the alternative hypothesis.

method

character string indicating the name of the goodness-of-fit test (e.g.,
"Shapiro-Wilk GOF").

data.name

character string indicating the name of the data object used for the goodness-of-fit test.

censored

logical vector indicating which observations are censored.

censoring.name

character string indicating the name of the object used to indicate the censoring.

Optional Components
The following components are included when the argument keep.data is set to TRUE in the call to the function producing the object of class "gofCensored".

data

numeric vector containing the data actually used for the goodness-of-fit test (i.e., the original data without any missing or infinite values).

censored

logical vector indicating the censoring status of the data actually used for the goodness-of-fit test.

The following component is included when the data object contains missing (NA), undefined (NaN) and/or infinite (Inf, -Inf) values.

bad.obs

numeric scalar indicating the number of missing (NA), undefined (NaN) and/or infinite (Inf, -Inf) values that were removed from the data object prior to performing the goodness-of-fit test.

Methods

Generic functions that have methods for objects of class "gofCensored" include:
print, plot.

Note

Since objects of class "gofCensored" are lists, you may extract their components with the $ and [[ operators.

Author(s)

Steven P. Millard ([e-mail])

See Also

gofTestCensored, print.gofCensored, plot.gofCensored, Censored Data, Goodness-of-Fit Tests, Distribution.df, gof.object.

Examples

  # Create an object of class "gofCensored", then print it out. 
  #------------------------------------------------------------

  gofCensored.obj <- with(EPA.09.Ex.15.1.manganese.df,
    gofTestCensored(Manganese.ppb, Censored, test = "sf"))

  mode(gofCensored.obj) 
  #[1] "list" 

  class(gofCensored.obj) 
  #[1] "gofCensored" 

  names(gofCensored.obj) 
  # [1] "distribution"            "dist.abb"               
  # [3] "distribution.parameters" "n.param.est"            
  # [5] "estimation.method"       "statistic"              
  # [7] "sample.size"             "censoring.side"         
  # [9] "censoring.levels"        "percent.censored"       
  #[11] "parameters"              "z.value"                
  #[13] "p.value"                 "alternative"            
  #[15] "method"                  "data"                   
  #[17] "data.name"               "censored"               
  #[19] "censoring.name"          "bad.obs" 

  gofCensored.obj 
  
  #Results of Goodness-of-Fit Test
  #Based on Type I Censored Data
  #-------------------------------
  #
  #Test Method:                     Shapiro-Francia GOF
  #                                 (Multiply Censored Data)
  #
  #Hypothesized Distribution:       Normal
  #
  #Censoring Side:                  left
  #
  #Censoring Level(s):              2 5 
  #
  #Estimated Parameter(s):          mean = 15.23508
  #                                 sd   = 30.62812
  #
  #Estimation Method:               MLE
  #
  #Data:                            Manganese.ppb
  #
  #Censoring Variable:              Censored
  #
  #Sample Size:                     25
  #
  #Percent Censored:                24%
  #
  #Test Statistic:                  W = 0.8368016
  #
  #Test Statistic Parameters:       N     = 25.00
  #                                 DELTA =  0.24
  #
  #P-value:                         0.004662658
  #
  #Alternative Hypothesis:          True cdf does not equal the
  #                                 Normal Distribution.

  #==========

  # Extract the p-value
  #--------------------

  gofCensored.obj$p.value
  #[1] 0.004662658

  #==========

  # Plot the results of the test
  #-----------------------------

  dev.new()
  plot(gofCensored.obj)

  #==========

  # Clean up
  #---------
  rm(gofCensored.obj)
  graphics.off()