Test of independence between two sets of variables. Inference is based on the spatial signs of the observations, symmetrized signs of the observations or spatial signed ranks of the observations.

1 2 3 |

`X` |
a matrix or a data frame |

`Y` |
an optional matrix or a data frame |

`g` |
a factor giving the two sets of variables, or numeric vector or vector of column names giving the first set of variables. See details |

`score` |
a character string indicating which transformation of the observations should be used |

`regexp` |
logical. Is |

`cond` |
logical. Should the conditionally distribution free test be used? |

`cond.n` |
Number of permutations to use in the conditionally distribution free test |

`na.action` |
a function which indicates what should happen when the data contain 'NA's. Default is to fail. |

`X`

should contain the first set of variables and
`Y`

the second with matching rows. Alternatively, `X`

should
contain both sets and `g`

should be a factor of length equal to
number of columns of `X`

, or, `g`

should be a numeric or
character vector naming the variables in the first set. If `g`

is
a character vector it is assumed to name all wanted columns exactly,
unless `regexp`

is `TRUE`

.

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

`statistic ` |
the value of the statistic |

`parameter` |
the degrees of freedom for the statistic or the number of replications if conditionally distribution free p-value was used |

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

`null.value` |
the specified hypothesized value of the measure of dependence (always 0) |

`alternative` |
a character string with the value 'two.sided'. |

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

`data.name` |
a character string giving the name of the data (and grouping vector) |

Seija Sirkia, seija.sirkia@iki.fi

Taskinen, S., Oja, H., Randles R. (2004) Multivariate Nonparametric Tests of Independence. *JASA*, 100, 916-925

Spatial signs and ranks

1 2 3 4 5 6 7 8 9 10 11 | ```
A<-matrix(c(1,2,-3,4,3,-2,-1,0,4),ncol=3)
X<-matrix(rnorm(3000),ncol=3)%*%t(A)
Y<-cbind(X+runif(3000,-1,1),runif(1000))
sr.indep.test(X,Y)
#alternative calls:
Z<-cbind(X,Y)
colnames(Z)<-c("a1","a2","a3","b1","b2","b3","b4")
g<-factor(c(rep(1,3),rep(2,4)))
sr.indep.test(Z,g=g)
sr.indep.test(Z,g=c("b"),regexp=TRUE)
sr.indep.test(Z,g=1:3)
``` |

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