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Calculate unbiased estimates of central moments and their powers and products.
uM6(m2, m3, m4, m6, n)
naive biased variance estimate \(m_2 = 1/n \sum_{i = 1}^n ((X_i - \bar{X})^2\) for a vector X.
X
naive biased third central moment estimate \(m_3 = 1/n \sum_{i = 1}^n ((X_i - \bar{X})^3\) for a vector X.
naive biased fourth central moment estimate \(m_4 = 1/n \sum_{i = 1}^n ((X_i - \bar{X})^4\) for a vector X.
naive biased sixth central moment estimate \(m_6 = 1/n \sum_{i = 1}^n ((X_i - \bar{X})^6\) for a vector X.
sample size.
Unbiased estimate of a sixth central moment.
Other unbiased estimates (one-sample): uM2M3, uM2M4, uM2pow2, uM2pow3, uM2, uM3pow2, uM3, uM4, uM5
uM2M3
uM2M4
uM2pow2
uM2pow3
uM2
uM3pow2
uM3
uM4
uM5
# NOT RUN { n <- 10 smp <- rgamma(n, shape = 3) m <- mean(smp) for (j in 2:6) { m <- c(m, mean((smp - m[1])^j)) } uM6(m[2], m[3], m[4], m[6], n) # }
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