Description Usage Arguments Value References Examples

Performs an independence test when it is assumed that the marginal distribution of *Y* is known and can be simulated from.

1 |

`x` |
The |

`y` |
The |

`k` |
The value of |

`ky` |
The value of |

`w` |
The weight vector to used for estimation of the joint entropy |

`wy` |
The weight vector to used for estimation of the marginal entropy |

`y0` |
The data matrix of simulated |

The *p*-value corresponding the independence test carried out.

2017arXiv171106642BIndepTest

1 2 3 4 5 6 7 8 9 10 11 12 | ```
library(mvtnorm)
x=rnorm(1000); y=rnorm(1000);
# Independent univariate normal data
MINTknown(x,y,k=20,ky=30,y0=rnorm(100000))
library(mvtnorm)
# Dependent univariate normal data
data=rmvnorm(1000,sigma=matrix(c(1,0.5,0.5,1),ncol=2))
# Dependent multivariate normal data
MINTknown(data[,1],data[,2],k=20,ky=30,y0=rnorm(100000))
Sigma=matrix(c(1,0,0,0,0,1,0,0,0,0,1,0.5,0,0,0.5,1),ncol=4)
data=rmvnorm(1000,sigma=Sigma)
MINTknown(data[,1:3],data[,4],k=20,ky=30,w=TRUE,wy=FALSE,y0=rnorm(100000))
``` |

IndepTest documentation built on May 1, 2019, 10:24 p.m.

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