Description Usage Arguments Details Value References See Also Examples

Compute the essential histogram via (pruned) dynamic programming.

1 2 | ```
essHistogram(x, alpha = 0.5, q = NA, plot = TRUE, verbose = TRUE,
xname = deparse(substitute(x)), ...)
``` |

`x` |
a numeric vector containing the data. |

`alpha` |
significance level; if |

`q` |
threshold value. |

`plot` |
logical. If |

`verbose` |
logical. If |

`xname` |
a character string with the actual |

`...` |
further arguments and |

The essential histogram is defined as the histogram with least blocks within the multiscale constraint. The one with highest likelihood is picked if there are more than one solutions. The essential histogram involves only one parameter `q`

, the threshold of the multiscale constraint. Such a parameter can be chosen by means of the significance level `alpha`

, which leads to nature statistical significance statements for the multiscale constraint. See Li et al. (2016) for further details.

An object of class "`histogram`

", which is of the same class as returned by function `hist`

.

Li, H., Munk, A., Sieling, H., and Walther, G. (2016). The essential histogram. arXiv:1612.07216.

1 2 3 4 5 6 7 | ```
# simulate data
set.seed(123)
n = 300
x = rnorm(n)
# compute the essential histogram
eh = essHistogram(x, xname = "Gauss")
``` |

essHist documentation built on April 9, 2018, 5:04 p.m.

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