SignTest
Sign Test
Performs one and twosample sign tests on vectors of data.
 Keywords
 htest
Usage
SignTest(x, ...)
"SignTest"(x, y = NULL, alternative = c("two.sided", "less", "greater"), mu = 0, conf.level = 0.95, ... )
"SignTest"(formula, data, subset, na.action, ...)
Arguments
 x
 numeric vector of data values. Nonfinite (e.g. infinite or missing) values will be omitted.
 y
 an optional numeric vector of data values: as with x nonfinite values will be omitted.
 mu
 a number specifying an optional parameter used to form the null hypothesis. See Details.
 alternative
 is a character string, one of
"greater"
,"less"
, or"two.sided"
, or the initial letter of each, indicating the specification of the alternative hypothesis. For onesample tests,alternative
refers to the true median of the parent population in relation to the hypothesized value of the median.  conf.level
 confidence level for the returned confidence interval, restricted to lie between zero and one.
 formula
 a formula of the form
lhs ~ rhs
wherelhs
gives the data values and rhs the corresponding groups.  data
 an optional matrix or data frame (or similar: see
model.frame
) containing the variables in the formulaformula
. By default the variables are taken fromenvironment(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 NAs. Defaults to
getOption("na.action")
.  ...
 further arguments to be passed to or from methods.
Details
The formula interface is only applicable for the 2sample test.
SignTest
computes a “Dependentsamples SignTest” if both
x
and y
are provided. If only x
is provided,
the “Onesample SignTest” will be computed.
For the onesample signtest, the null hypothesis is
that the median of the population from which x
is drawn is mu
.
For the twosample dependent case, the null hypothesis is
that the median for the differences of the populations from which x
and y
are drawn is mu
.
The alternative hypothesis indicates the direction of divergence of the
population median for x
from mu
(i.e., "greater"
,
"less"
, "two.sided"
.)
The confidence levels are exact.
Value

A list of class
htest
, containing the following components:References
Gibbons, J.D. and Chakraborti, S. (1992): Nonparametric Statistical Inference. Marcel Dekker Inc., New York.
Kitchens, L. J. (2003): Basic Statistics and Data Analysis. Duxbury.
Conover, W. J. (1980): Practical Nonparametric Statistics, 2nd ed. Wiley, New York.
See Also
t.test
, wilcox.test
, ZTest
, binom.test
,
SIGN.test
in the package BSDA (reporting approximative confidence intervals).
Examples
x < c(1.83, 0.50, 1.62, 2.48, 1.68, 1.88, 1.55, 3.06, 1.30)
y < c(0.878, 0.647, 0.598, 2.05, 1.06, 1.29, 1.06, 3.14, 1.29)
SignTest(x, y)
wilcox.test(x, y, paired = TRUE)
d.light < data.frame(
black = c(25.85,28.84,32.05,25.74,20.89,41.05,25.01,24.96,27.47),
white < c(18.23,20.84,22.96,19.68,19.5,24.98,16.61,16.07,24.59),
d < c(7.62,8,9.09,6.06,1.39,16.07,8.4,8.89,2.88)
)
d < d.light$d
SignTest(x=d, mu = 4)
wilcox.test(x=d, mu = 4, conf.int = TRUE)
SignTest(x=d, mu = 4, alternative="less")
wilcox.test(x=d, mu = 4, conf.int = TRUE, alternative="less")
SignTest(x=d, mu = 4, alternative="greater")
wilcox.test(x=d, mu = 4, conf.int = TRUE, alternative="greater")
# test die interfaces
x < runif(10)
y < runif(10)
g < rep(1:2, each=10)
xx < c(x, y)
SignTest(x ~ group, data=data.frame(x=xx, group=g ))
SignTest(xx ~ g)
SignTest(x, y)
SignTest(x  y)