# the Differents-Sign Test of Statistical Independence

### Description

Tests for a trend in a data series by comparing the number of positive differences between successive elements in the series to the number expected in an i.i.d. series.

### Usage

1 |

### Arguments

`x` |
a numeric vector or univariate time series. |

### Details

Perform a test for trend based on the signs of successive differences in a data series. #this function counts the number of positive successive differences in the data, standardises #it to have mean 0 and variance 1 and asymptotically tests it against a standard normal distribution. the test statistic is:

D = (pd - mu)/sigma, where

pd is the number of positive differences in the data series,

mu = (n-1)/2,

sigma = sqrt((n+1)/12) and

n is the number of points in the data series.

The test is set up as follows:

*H0*: the data series is i.i.d. (not trending)

*H1*: the data series is not i.i.d. (trending)

### Value

A list with class "htest" containing the following components:

`statistic` |
the value of the test statistic. |

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

`method` |
a character string indicating what type of test was performed. |

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

`n` |
the number of points in the data series. |

`mu` |
The expected number of positive differences that would be seen in an i.i.d. series. |

`sigma` |
The standard deviation of the number of positive differences that would be seen in an i.i.d. series. |

### Note

Missing values are not handled.

Points followed by a point having the exact same value are removed from the data series before computing the test statistic.

This test is useful for detecting linear trends in data series.

### Author(s)

Andrew Hart and Servet Mart<ed>nez

### References

Brockwell, Peter J., Davis, Richard A. (2002) *Introduction to Time Series and Forecasting*.
Springer Texts in Statistics, Springer-Verlag, New York.

### See Also

`turningpoint.test`

, `rank.test`

, `lb.test`

`markov.test`

, `diid.test`

,

### Examples

1 2 3 | ```
#Generate an IID standard normal sequence
n <- rnorm(1000)
diffsign.test(n)
``` |

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