Calculates the approximate standard error of the sample variance, sample central third moment and sample central fourth moment.

1 |

`order` |
Integer: either 2, 3, or 4. |

`n` |
Integer: the sample size. |

`mom` |
Numeric: The central moments of order 1 to |

Implements the approximate standard error given in Kendall and Stuart (1969), p.243.

The approximate standard error of the sample moment specified.

David Scott d.scott@auckland.ac.nz

Kendall, M. G. and Stuart, A. (1969).
*The Advanced Theory of Statistics, Volume 1, 3rd Edition*.
London: Charles Griffin & Company.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 | ```
### Moments of the normal distribution, mean 1, variance 4
mu <- 1
sigma <- 2
mom <- c(0,sigma^2,0,3*sigma^4,0,15*sigma^6,0,105*sigma^8)
### standard error of sample variance
momSE(2, 100, mom[1:4])
### should be
sqrt(2*sigma^4)/10
### standard error of sample central third moment
momSE(3, 100, mom[1:6])
### should be
sqrt(6*sigma^6)/10
### standard error of sample central fourth moment
momSE(4, 100, mom)
### should be
sqrt(96*sigma^8)/10
``` |

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