Last updated on 2026-06-04 18:50:13 CEST.
| Flavor | Version | Tinstall | Tcheck | Ttotal | Status | Flags |
|---|---|---|---|---|---|---|
| r-devel-linux-x86_64-debian-clang | 1.2-0 | 2.70 | 41.76 | 44.46 | OK | |
| r-devel-linux-x86_64-debian-gcc | 1.2-0 | 2.04 | 30.21 | 32.25 | OK | |
| r-devel-linux-x86_64-fedora-clang | 1.2-0 | 70.92 | OK | |||
| r-devel-linux-x86_64-fedora-gcc | 1.2-0 | 76.88 | WARN | |||
| r-devel-windows-x86_64 | 1.2-0 | 4.00 | 89.00 | 93.00 | OK | |
| r-patched-linux-x86_64 | 1.2-0 | 2.93 | 39.41 | 42.34 | OK | |
| r-release-linux-x86_64 | 1.2-0 | 2.66 | 39.69 | 42.35 | OK | |
| r-release-macos-arm64 | 1.2-0 | 1.00 | 18.00 | 19.00 | OK | |
| r-release-macos-x86_64 | 1.2-0 | 2.00 | 68.00 | 70.00 | OK | |
| r-release-windows-x86_64 | 1.2-0 | 4.00 | 94.00 | 98.00 | OK | |
| r-oldrel-macos-arm64 | 1.2-0 | OK | ||||
| r-oldrel-macos-x86_64 | 1.2-0 | 2.00 | 94.00 | 96.00 | OK | |
| r-oldrel-windows-x86_64 | 1.2-0 | 4.00 | 88.00 | 92.00 | OK |
Version: 1.2-0
Check: re-building of vignette outputs
Result: WARN
Error(s) in re-building vignettes:
--- re-building ‘OneTwoSamples.Rnw’ using Sweave
data_outline package:OneTwoSamples R Documentation
_<08>C_<08>o_<08>m_<08>p_<08>u_<08>t_<08>e _<08>v_<08>a_<08>r_<08>i_<08>o_<08>u_<08>s _<08>d_<08>e_<08>s_<08>c_<08>r_<08>i_<08>p_<08>t_<08>i_<08>v_<08>e _<08>s_<08>t_<08>a_<08>t_<08>i_<08>s_<08>t_<08>i_<08>c_<08>s
_<08>D_<08>e_<08>s_<08>c_<08>r_<08>i_<08>p_<08>t_<08>i_<08>o_<08>n:
Compute various descriptive statistics of x, such as mean, median,
skewness, and kurtosis, etc.
_<08>U_<08>s_<08>a_<08>g_<08>e:
data_outline(x)
_<08>A_<08>r_<08>g_<08>u_<08>m_<08>e_<08>n_<08>t_<08>s:
x: A numeric vector.
_<08>V_<08>a_<08>l_<08>u_<08>e:
A data.frame with variables:
N: The length.
Mean: The mean.
Var: The variance.
std_dev: Standard deviation.
Median: The median.
std_mean: The standard error of the sample mean.
CV: The coefficient of variation.
CSS: The corrected sum of squares.
USS: The uncorrected sum of squares.
R: The extreme difference.
R1: The half extreme difference, or the difference of upper
quartile and lower quartile.
Skewness: The coefficient of skewness.
Kurtosis: The coefficient of kurtosis.
row.names: 1.
_<08>A_<08>u_<08>t_<08>h_<08>o_<08>r(_<08>s):
Ying-Ying Zhang (Robert) <mailto:robertzhangyying@qq.com>
_<08>R_<08>e_<08>f_<08>e_<08>r_<08>e_<08>n_<08>c_<08>e_<08>s:
Zhang, Y. Y., Wei, Y. (2013), One and two samples using only an R
funtion, doi:10.2991/asshm-13.2013.29
<https://doi.org/10.2991/asshm-13.2013.29>.
_<08>E_<08>x_<08>a_<08>m_<08>p_<08>l_<08>e_<08>s:
x=rnorm(10, mean = 1, sd = 0.2); x
data_outline(x)
t.test package:stats R Documentation
_<08>S_<08>t_<08>u_<08>d_<08>e_<08>n_<08>t'_<08>s _<08>t-_<08>T_<08>e_<08>s_<08>t
_<08>D_<08>e_<08>s_<08>c_<08>r_<08>i_<08>p_<08>t_<08>i_<08>o_<08>n:
Performs one and two sample t-tests on vectors of data.
_<08>U_<08>s_<08>a_<08>g_<08>e:
t.test(x, ...)
## Default S3 method:
t.test(x, y = NULL,
alternative = c("two.sided", "less", "greater"),
mu = 0, paired = FALSE, var.equal = FALSE,
conf.level = 0.95, ...)
## S3 method for class 'formula'
t.test(formula, data, subset, na.action = na.pass, ...)
_<08>A_<08>r_<08>g_<08>u_<08>m_<08>e_<08>n_<08>t_<08>s:
x: a (non-empty) numeric vector of data values.
y: an optional (non-empty) numeric vector of data values.
alternative: a character string specifying the alternative hypothesis,
must be one of ‘"two.sided"’ (default), ‘"greater"’ or
‘"less"’. You can specify just the initial letter.
mu: a number indicating the true value of the mean (or difference
in means if you are performing a two sample test).
paired: a logical indicating whether you want a paired t-test.
var.equal: a logical variable indicating whether to treat the two
variances as being equal. If ‘TRUE’ then the pooled variance
is used to estimate the variance otherwise the Welch (or
Satterthwaite) approximation to the degrees of freedom is
used.
conf.level: confidence level of the interval.
formula: a formula of the form ‘lhs ~ rhs’ where ‘lhs’ is a numeric
variable giving the data values and ‘rhs’ either ‘1’ for a
one-sample or paired test or a factor with two levels giving
the corresponding groups. If ‘lhs’ is of class ‘"Pair"’ and
‘rhs’ is ‘1’, a paired test is done, see Examples.
data: an optional matrix or data frame (or similar: see
‘model.frame’) containing the variables in the formula
‘formula’. By default the variables are taken from
‘environment(formula)’.
subset: an optional vector specifying a subset of observations to be
used.
na.action: a function which indicates what should happen when the data
contain ‘NA’s.
...: further arguments to be passed to or from methods. For the
‘formula’ method, this includes arguments of the default
method, but not ‘paired’.
_<08>D_<08>e_<08>t_<08>a_<08>i_<08>l_<08>s:
‘alternative = "greater"’ is the alternative that ‘x’ has a larger
mean than ‘y’. For the one-sample case: that the mean is positive.
If ‘paired’ is ‘TRUE’ then both ‘x’ and ‘y’ must be specified and
they must be the same length. Missing values are silently removed
(in pairs if ‘paired’ is ‘TRUE’). If ‘var.equal’ is ‘TRUE’ then
the pooled estimate of the variance is used. By default, if
‘var.equal’ is ‘FALSE’ then the variance is estimated separately
for both groups and the Welch modification to the degrees of
freedom is used.
If the input data are effectively constant (compared to the larger
of the two means) an error is generated.
If the data contain infinite values, ‘t.test()’ no longer errors
and returns a still not very useful result. Note that
‘wilcox.test()’ is _robust_ against outliers and hence deals more
usefully with such ‘Inf’ values in ‘x’ or ‘y’.
_<08>V_<08>a_<08>l_<08>u_<08>e:
A list with class ‘"htest"’ containing the following components:
statistic: the value of the t-statistic.
parameter: the degrees of freedom for the t-statistic.
p.value: the p-value for the test.
conf.int: a confidence interval for the mean appropriate to the
specified alternative hypothesis.
estimate: the estimated mean or difference in means depending on
whether it was a one-sample test or a two-sample test.
null.value: the specified hypothesized value of the mean or mean
difference depending on whether it was a one-sample test or a
two-sample test.
stderr: the standard error of the mean (difference), used as
denominator in the t-statistic formula.
alternative: a character string describing the alternative hypothesis.
method: a character string indicating what type of t-test was
performed.
data.name: a character string giving the name(s) of the data.
_<08>S_<08>e_<08>e _<08>A_<08>l_<08>s_<08>o:
‘prop.test’
_<08>E_<08>x_<08>a_<08>m_<08>p_<08>l_<08>e_<08>s:
## Two-sample t-test
t.test(1:10, y = c(7:20)) # P = .00001855
t.test(1:10, y = c(7:20, 200)) # P = .1245 -- NOT significant anymore
## Traditional interface
with(mtcars, t.test(mpg[am == 0], mpg[am == 1]))
## Formula interface
t.test(mpg ~ am, data = mtcars)
## One-sample t-test
## Traditional interface
t.test(sleep$extra)
## Formula interface
t.test(extra ~ 1, data = sleep)
## Paired t-test
## The sleep data is actually paired, so could have been in wide format:
sleep2 <- reshape(sleep, direction = "wide",
idvar = "ID", timevar = "group")
## Traditional interface
t.test(sleep2$extra.1, sleep2$extra.2, paired = TRUE)
## Formula interface
t.test(Pair(extra.1, extra.2) ~ 1, data = sleep2)
dev.new(): using pdf(file="Rplots1.pdf")
dev.new(): using pdf(file="Rplots2.pdf")
dev.new(): using pdf(file="Rplots3.pdf")
dev.new(): using pdf(file="Rplots4.pdf")
dev.new(): using pdf(file="Rplots5.pdf")
dev.new(): using pdf(file="Rplots6.pdf")
dev.new(): using pdf(file="Rplots7.pdf")
dev.new(): using pdf(file="Rplots8.pdf")
dev.new(): using pdf(file="Rplots9.pdf")
dev.new(): using pdf(file="Rplots10.pdf")
dev.new(): using pdf(file="Rplots11.pdf")
Error: processing vignette 'OneTwoSamples.Rnw' failed with diagnostics:
Running 'texi2dvi' on 'OneTwoSamples.tex' failed.
LaTeX errors:
! Undefined control sequence.
\tabu@cleanup ...bu@naturalX =\tabu@naturalX@save
\let \tabu@naturalXmax \ta...
l.198 \end{tabu}
! Emergency stop.
\tabu@cleanup ...bu@naturalX =\tabu@naturalX@save
\let \tabu@naturalXmax \ta...
l.198 \end{tabu}
! ==> Fatal error occurred, no output PDF file produced!
--- failed re-building ‘OneTwoSamples.Rnw’
SUMMARY: processing the following file failed:
‘OneTwoSamples.Rnw’
Error: Vignette re-building failed.
Execution halted
Flavor: r-devel-linux-x86_64-fedora-gcc