Description Details Value Methods Note Author(s) See Also Examples

Objects of S3 class `"gofGroup"`

are returned by the EnvStats function
`gofGroupTest`

.

Objects of S3 class `"gofGroup"`

are lists that contain
information about the assumed distribution, the estimated or
user-supplied distribution parameters, and the test statistic
and p-value.

**Required Components**

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

.

`distribution` |
a character string indicating the name of the
assumed distribution (see |

`dist.abb` |
a character string containing the abbreviated name
of the distribution (see |

`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. |

`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 |

`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., |

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

`grouping.variable` |
character string indicating the name of the variable defining the groups. |

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

`n.groups` |
numeric scalar containing the number of groups. |

`group.names` |
character vector containing the levels of the grouping variable, i.e., the names of each of the groups. |

`group.scores` |
numeric vector containing the individual statistics for each group. |

**Optional Component**

The following component is included when `gofGroupTest`

is
called with a formula for the first argument and a `data`

argument.

`parent.of.data` |
character string indicating the name of the object supplied
in the |

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

include:

`print`

, `plot`

.

Since objects of class `"gofGroup"`

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

and `[[`

operators.

Steven P. Millard ([email protected])

`gofGroupTest`

, `print.gofGroup`

, `plot.gofGroup`

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

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 | ```
# Create an object of class "gofGroup", then print it out.
# Example 10-4 of USEPA (2009, page 10-20) gives an example of
# simultaneously testing the assumption of normality for nickel
# concentrations (ppb) in groundwater collected at 4 monitoring
# wells over 5 months. The data for this example are stored in
# EPA.09.Ex.10.1.nickel.df.
gofGroup.obj <- gofGroupTest(Nickel.ppb ~ Well,
data = EPA.09.Ex.10.1.nickel.df)
mode(gofGroup.obj)
#[1] "list"
class(gofGroup.obj)
#[1] "gofGroup"
names(gofGroup.obj)
# [1] "distribution" "dist.abb" "statistic"
# [4] "sample.size" "parameters" "p.value"
# [7] "alternative" "method" "data.name"
#[10] "grouping.variable" "parent.of.data" "bad.obs"
#[13] "n.groups" "group.names" "group.scores"
gofGroup.obj
#Results of Group Goodness-of-Fit Test
#-------------------------------------
#
#Test Method: Wilk-Shapiro GOF (Normal Scores)
#
#Hypothesized Distribution: Normal
#
#Data: Nickel.ppb
#
#Grouping Variable: Well
#
#Data Source: EPA.09.Ex.10.1.nickel.df
#
#Number of Groups: 4
#
#Sample Sizes: Well.1 = 5
# Well.2 = 5
# Well.3 = 5
# Well.4 = 5
#
#Test Statistic: z (G) = -3.658696
#
#P-values for
#Individual Tests: Well.1 = 0.03510747
# Well.2 = 0.02385344
# Well.3 = 0.01120775
# Well.4 = 0.10681461
#
#P-value for
#Group Test: 0.0001267509
#
#Alternative Hypothesis: At least one group
# does not come from a
# Normal Distribution.
#==========
# Extract the p-values
#---------------------
gofGroup.obj$p.value
# Well.1 Well.2 Well.3 Well.4 z (G)
#0.0351074733 0.0238534406 0.0112077511 0.1068146088 0.0001267509
#==========
# Plot the results of the test
#-----------------------------
dev.new()
plot(gofGroup.obj)
#==========
# Clean up
#---------
rm(gofGroup.obj)
graphics.off()
``` |

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