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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