plotPI | R Documentation |

This function creates scatterplot matrices for the different probabilistic indices (PI) `P_t`

, `P_{tt'}`

and `P_{tt't''}`

computed for different variables.

```
plotPI(X,g,type="pair",goi=NULL,mc=1,alg="Cnaive",col="black",
highlight=NULL,hlCol="red",pch=20,zoom=FALSE,order=NULL,...)
```

`X` |
Matrix or vector with observations. Each column is a variable, each row an individual. |

`g` |
Vector of group labels for observations in |

`type` |
Type of probabilistic index, see details. |

`goi` |
Groups of Interest, see details. |

`mc` |
Set the amount of cores to use for parallel calculation (only available for Linux). |

`order` |
Boolean, calculate PI only for natural order or for all combinations. |

`alg` |
Internal function, which implementation should be used to calculate the PI. |

`col` |
Vector of colors of the scatterplot. |

`highlight` |
Vector with positions, which are marked in special color. |

`hlCol` |
Color of highlighted spots. |

`pch` |
Dot type of the plot. |

`zoom` |
Logical, shall the plots be zoomed to interesting areas? |

`...` |
Additional plotting arguments. |

This function creates the scatterplot matrices for the PI, in case that they haven't
been calculated previoulsy. This means that all arguments of the `estPI`

are valid here, since
this function is called first and the results will then be passed to the plot function of the `estPI`

object.

See also `plot.estPI`

for further details on the specific plot parameters.

A plot of probalistic indices

Daniel Fischer

Fischer, D., Oja, H., Schleutker, J., Sen, P.K., Wahlfors, T. (2013): Generalized Mann-Whitney Type Tests for Microarray Experiments, Scandinavian Journal of Statistic, to appear.

Fischer, D., Oja, H. (2013): Mann-Whitney Type Tests for Microarray Experiments: The R Package gMWT, submitted article.

`estPI`

, `plot.estPI`

```
X <- c(sample(15))
g <- c(1,1,1,2,2,2,2,3,3,3,4,4,4,4,4)
estPI(X,g,type="single")
X <- matrix(c(rnorm(5000,1.5,2),rnorm(6000,2,2),rnorm(4000,3.5,1)),byrow=TRUE, ncol=10)
colnames(X) <- letters[1:10]
g <- c(rep(1,500),rep(2,600),rep(3,400))
plotPI(X,g,type="single",mc=1)
```

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