Description Usage Arguments Details Value Note Author(s) References Examples

Perform sign test on one-sample data, which is one of the oldest non-parametric statistical methods. Assume that X comes from a continuous distribution with median = v ( unknown ). Test the null hypothesis H0: median of X v = mu ( mu is the location parameter and is given in the test ) v.s. the alternative hypothesis H1: v > mu ( or v < mu or v != mu ) and calculate the p-value. When the sample size is large, perform the asymptotic sign test. In both ways, calculate the R-estimate of location of X and the distribution free confidence interval for mu.

1 2 3 4 |

`x` |
numeric vector of data values. |

`mu` |
the location parameter, it is a number specifying an optional parameter used to form the null hypothesis. |

`alternative` |
a character string specifying the alternative hypothesis, must be one of "two.sided" , "greater" or "less". You can specify just the initial letter. |

`conf.level` |
confidence level of the confidence interval. |

`exact` |
a logical indicating whether an exact p-value should be computed. |

`...` |
further arguments to be passed to or from methods. |

This is a simple non-parametric statistical method. Perform simple sign test on one-sample data like wilcox.test without ranking. Assume that X comes from a continuous distribution with median = v ( unknown ). Test the null hypothesis H0: median of X v = mu ( mu is given in the test ) v.s. the alternative hypothesis H1: v > mu ( or v < mu or v != mu ) and calculate the p-value. When the sample size is large, perform the asymptotic sign test( with continuity correction ). In both exact and asymptotic sign tests, calculate the R-estimate of location of X and the distribution free confidence interval for location parameter mu. This can also perform a test of the paired data ( X, Y ) if we redefine X with Y-X.

`statistic` |
the value of the test statistic with a name describing it. |

`parameter` |
the location parameter mu. |

`p.value` |
the p-value for the test. |

`alternative` |
a character string describing the alternative hypothesis. |

`conf.int` |
a confidence interval for the location parameter. |

`estimate` |
an estimate of the location parameter. |

`method` |
the type of test applied. |

`data.name` |
a character string giving the names of the data. |

If you want to perform a test of the paired data ( X, Y ), please redefine X with Y-X and then perform the test.

Ting Yang and Yeyun Yu

none.

1 2 3 4 5 6 7 8 9 | ```
##One-sample test
x<-c(-5,-3,-2,1,5,6,3,9,10,15,20,21)
signmedian.test(x,alternative = "greater",exact=TRUE)
signmedian.test(x,mu=3,alternative="two.sided",exact=FALSE)
##Two-sample test(paired data)
x<-c(-5,-3,-2,1,5,6,3,9,10,15,20,21)
y<-c(-1,-2,-3,1,2,3,4,2,6,8,9,10)
x<-y-x
signmedian.test(x,alternative = "greater",exact=TRUE)
``` |

```
Exact sign test
data: x
#(x>0) = 9, mu = 0, p-value = 0.073
alternative hypothesis: the median of x is greater than mu
96.14258 percent confidence interval:
-2 15
sample estimates:
point estimator
5.5
Asymptotic sign test(with continuity correction)
data: x
#(x!=3) = 11, mu = 3, p-value = 0.5465
alternative hypothesis: the median of x is not equal to mu
94.79071 percent confidence interval:
-3 20
sample estimates:
point estimator
5.5
Exact sign test
data: x
#(x>0) = 3, mu = 0, p-value = 0.9673
alternative hypothesis: the median of x is greater than mu
93.45703 percent confidence interval:
-7 1
sample estimates:
point estimator
-3
```

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