gofGroup.object.RdObjects 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".
a character string indicating the name of the
assumed distribution (see Distribution.df).
a character string containing the abbreviated name
of the distribution (see Distribution.df).
a numeric scalar with a names attribute containing the name and value of the goodness-of-fit statistic.
a numeric scalar containing the number of non-missing observations in the sample used for the goodness-of-fit test.
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.
numeric scalar containing the p-value associated with the goodness-of-fit statistic.
character string indicating the alternative hypothesis.
character string indicating the name of the
goodness-of-fit test (e.g., "Wilk-Shapiro GOF (Normal Scores)").
character string indicating the name of the data object used for the goodness-of-fit test.
character string indicating the name of the variable defining the groups.
numeric vector indicating the number of missing (NA),
undefined (NaN) and/or infinite (Inf, -Inf)
values that were removed from each group and the grouping variable
prior to performing the goodness-of-fit test.
numeric scalar containing the number of groups.
character vector containing the levels of the grouping variable, i.e., the names of each of the groups.
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.
character string indicating the name of the object supplied
in the data argument.
Since objects of class "gofGroup" are lists, you may extract
their components with the $ and [[ operators.
# 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"
#[1] "list"
class(gofGroup.obj)
#> [1] "gofGroup"
#[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"
# [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.
#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
# 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()