distChoose.object | R Documentation |

Objects of S3 class `"distChoose"`

are returned by the EnvStats function
`distChoose`

.

Objects of S3 class `"distChoose"`

are lists that contain
information about the candidate distributions, the estimated distribution
parameters for each candidate distribution, and the test statistics and
p-values associated with each candidate distribution.

**Required Components**

The following components must be included in a legitimate list of
class `"distChoose"`

.

`choices` |
a character vector containing the full names
of the candidate distributions. (see |

`method` |
a character string denoting which method was used. |

`decision` |
a character vector containing the full name of the chosen distribution. |

`alpha` |
a numeric scalar between 0 and 1 specifying the Type I error associated with each goodness-of-fit test. |

`distribution.parameters` |
a numeric vector containing the estimated parameters associated with the chosen distribution. |

`estimation.method` |
a character string indicating the method
used to compute the estimated parameters associated with the chosen
distribution. The value of this component will depend on the
available estimation methods (see |

`sample.size` |
a numeric scalar containing the number of non-missing observations in the sample used for the goodness-of-fit tests. |

`test.results` |
a list with the same number of components as the number
of elements in the component |

`data.name` |
character string indicating the name of the data object used for the goodness-of-fit tests. |

**Optional Components**

The following component is included in the result of
calling `distChoose`

when the argument `keep.data=TRUE`

:

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

The following component is included in the result of
calling `distChoose`

when missing (`NA`

),
undefined (`NaN`

) and/or infinite (`Inf`

, `-Inf`

)
values are present:

`bad.obs` |
numeric scalar indicating the number of missing ( |

Generic functions that have methods for objects of class
`"distChoose"`

include:

`print`

.

Since objects of class `"distChoose"`

are lists, you may extract
their components with the `$`

and `[[`

operators.

Steven P. Millard (EnvStats@ProbStatInfo.com)

`distChoose`

, `print.distChoose`

,
Goodness-of-Fit Tests,
`Distribution.df`

.

# Create an object of class "distChoose", then print it out. # (Note: the call to set.seed simply allows you to reproduce # this example.) set.seed(47) dat <- rgamma(20, shape = 2, scale = 3) distChoose.obj <- distChoose(dat) mode(distChoose.obj) #[1] "list" class(distChoose.obj) #[1] "distChoose" names(distChoose.obj) #[1] "choices" "method" #[3] "decision" "alpha" #[5] "distribution.parameters" "estimation.method" #[7] "sample.size" "test.results" #[9] "data" "data.name" distChoose.obj #Results of Choosing Distribution #-------------------------------- # #Candidate Distributions: Normal # Gamma # Lognormal # #Choice Method: Shapiro-Wilk # #Type I Error per Test: 0.05 # #Decision: Gamma # #Estimated Parameter(s): shape = 1.909462 # scale = 4.056819 # #Estimation Method: MLE # #Data: dat # #Sample Size: 20 # #Test Results: # # Normal # Test Statistic: W = 0.9097488 # P-value: 0.06303695 # # Gamma # Test Statistic: W = 0.9834958 # P-value: 0.970903 # # Lognormal # Test Statistic: W = 0.9185006 # P-value: 0.09271768 #========== # Extract the choices #-------------------- distChoose.obj$choices #[1] "Normal" "Gamma" "Lognormal" #========== # Clean up #--------- rm(dat, distChoose.obj)

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