htest.object {EnvStats}  R Documentation 
This class of objects is returned by functions that perform hypothesis tests
(e.g., the R function t.test
, the EnvStats function
kendallSeasonalTrendTest
, etc.).
Objects of class "htest"
are lists that contain information about the null
and alternative hypotheses, the estimated distribution parameters, the test statistic,
the pvalue, and (optionally) confidence intervals for distribution parameters.
Objects of S3 class "htest"
are returned by any of the
EnvStats functions that perform hypothesis tests as listed
here: Hypothesis Tests.
(Note that functions that perform goodnessoffit tests
return objects of class "gof"
or
"gofTwoSample"
.)
Objects of class "htest"
generated by EnvStats functions may
contain additional components called
estimation.method
(method used to estimate the population parameter(s)),
sample.size
, and
bad.obs
(number of missing (NA
), undefined (NaN
), or infinite
(Inf
, Inf
) values removed prior to performing the hypothesis test),
and interval
(a list with information about a confidence, prediction, or
tolerance interval).
Required Components
The following components must be included in a legitimate list of
class "htest"
.
null.value 
numeric vector containing the value(s) of the population parameter(s) specified by
the null hypothesis. This vector has a 
alternative 
character string indicating the alternative hypothesis (the value of the input
argument 
method 
character string giving the name of the test used. 
estimate 
numeric vector containing the value(s) of the estimated population parameter(s)
involved in the null hypothesis. This vector has a 
data.name 
character string containing the actual name(s) of the input data. 
statistic 
numeric scalar containing the value of the test statistic, with a

parameters 
numeric vector containing the parameter(s) associated with the null distribution of
the test statistic. This vector has a 
p.value 
numeric scalar containing the pvalue for the test under the null hypothesis. 
Optional Components
The following component may optionally be included in an object of
of class "htest"
generated by R functions that test hypotheses:
conf.int 
numeric vector of length 2 containing lower and upper confidence limits for the
estimated population parameter. This vector has an attribute called

The following components may be included in objects of class "htest"
generated by EnvStats functions:
sample.size 
numeric scalar containing the number of nonmissing observations in the sample used for the hypothesis test. 
estimation.method 
character string containing the method used to compute the estimated distribution
parameter(s). The value of this component will depend on the available estimation
methods (see 
bad.obs 
the number of missing ( 
interval 
a list containing information about a confidence, prediction, or tolerance interval. 
Generic functions that have methods for objects of class
"htest"
include:
print
.
Since objects of class "htest"
are lists, you may extract
their components with the $
and [[
operators.
Steven P. Millard (EnvStats@ProbStatInfo.com)
print.htest
, Hypothesis Tests.
# Create an object of class "htest", then print it out.
#
htest.obj < chenTTest(EPA.02d.Ex.9.mg.per.L.vec, mu = 30)
mode(htest.obj)
#[1] "list"
class(htest.obj)
#[1] "htest"
names(htest.obj)
# [1] "statistic" "parameters" "p.value" "estimate"
# [5] "null.value" "alternative" "method" "sample.size"
# [9] "data.name" "bad.obs" "interval"
htest.obj
#Results of Hypothesis Test
#
#
#Null Hypothesis: mean = 30
#
#Alternative Hypothesis: True mean is greater than 30
#
#Test Name: Onesample tTest
# Modified for
# PositivelySkewed Distributions
# (Chen, 1995)
#
#Estimated Parameter(s): mean = 34.566667
# sd = 27.330598
# skew = 2.365778
#
#Data: EPA.02d.Ex.9.mg.per.L.vec
#
#Sample Size: 60
#
#Test Statistic: t = 1.574075
#
#Test Statistic Parameter: df = 59
#
#Pvalues: z = 0.05773508
# t = 0.06040889
# Avg. of z and t = 0.05907199
#
#Confidence Interval for: mean
#
#Confidence Interval Method: Based on z
#
#Confidence Interval Type: Lower
#
#Confidence Level: 95%
#
#Confidence Interval: LCL = 29.82
# UCL = Inf
#==========
# Extract the test statistic
#
htest.obj$statistic
# t
#1.574075
#==========
# Clean up
#
rm(htest.obj)