pvalHist | R Documentation |

Graphical exploration of extreme p-values from quartet hypothesis tests, to aid in choosing critical values for hypothesis tests. Log base 10 of p-values exceeding some minimum are plotted, to explore gaps in the tail of the distribution.

pvalHist(pTable, model, pmin = 0)

`pTable` |
a quartet table with p-values, such as from |

`model` |
one of |

`pmin` |
include only p-values above |

Since logarithms are plotted, p-values close to 0 will appear as negative numbers of large magnitude, putting the tail of the distribution to the left in the histogram.

When exploring possible critical values for the hypothesis tests in the NANUQ algorithm, use `model= "T3"`

to
choose values for `alpha`

which distinguish treelikeness from hybridization, and `model= "star"`

to
choose values for `beta`

which distinguish polytomies from resolved trees.
In general, `alpha`

should be chosen to be small and `beta`

to be large so that most quartets are interpreted as resolved trees.

No return value, called for side effects

`NANUQ`

, `NANUQdist`

pTable=NANUQ(system.file("extdata","dataYeastRokas",package="MSCquartets"), alpha=0.05, beta=.95, outfile = file.path(tempdir(), "NANUQdist")) pvalHist(pTable,"T3")

MSCquartets documentation built on Dec. 10, 2022, 5:06 p.m.

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