Description Usage Arguments Details Value References See Also Examples

Compute moment-based statistics from probability distributions.

1 2 3 4 5 6 7 8 9 10 11 12 | ```
ph.mean (sf, ..., n.intervals=200)
ph.sd (sf, ..., n.intervals=200)
ph.var (sf, ..., n.intervals=200)
ph.skewness (sf, ..., n.intervals=200)
ph.kurtosis (sf, ..., n.intervals=200)
moment (sf, nth, ..., n.intervals=200)
central.moment (sf, nth, ..., n.intervals=200)
standardized.moment (sf, nth, ..., n.intervals=200)
raw.moment (sf, nth, about=0, ..., n.intervals=200)
``` |

`sf` |
A suitable function object. |

`nth` |
Integer, the nth moment |

.

`about` |
Numeric, the about constant for raw moments. |

`n.intervals` |
Integer. |

`...` |
Ignored. |

The mean/sd/var/skewness/kurtosis functions all call the moment function.

If the moment function is called with nth equal zero, it returns one.

If called with nth=1 (the mean), it computes the the first raw moment.

If called with nth=2 (the variance), it computes the second central moment.

If called with nth=3 (the skewness), it computes the third standardized moment.

If called with nth=4 (the kurtosis), it computes the fourth standardized moment.

And if called with nth>4, it also computes the nth standardized moment.

Note that currently, the standard deviation, variance and higher moments, should should not be regarded as accurate.

A single numeric value.

Refer to the vignette for an overview, references and better examples.

Succinct Constructors

Discrete Kernel Smoothing, Continuous Kernel Smoothing, Empirical-Like Distributions

probmv, rng

quartiles, ntiles, ph.median, ph.quantile

ph.mode, ph.modes

1 2 3 4 5 6 7 8 | ```
prep.ph.data ()
cFh <- cdfuv.cks (height)
ph.mean (cFh)
ph.sd (cFh)
ph.skewness (cFh)
ph.kurtosis (cFh)
``` |

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