Description Usage Arguments Details Value Author(s) References See Also Examples
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 2n of the distribution being sampled from. |
Implements the approximate standard error given in Kendall and Stuart (1969), p.243.
The approximate standard error of the sample moment specified.
David Scott [email protected]
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
|
Loading required package: RUnit
[1] 0.5656854
[1] 0.5656854
[1] 1.959592
[1] 1.959592
[1] 15.67673
[1] 15.67673
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