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Calculate unbiased estimates of central moments and their powers and products.
uM2pow2(m2, m4, n)
Unbiased estimate of squared variance \(\mu_2^2\), where
\(\mu_2\) is a variance.
naive biased variance estimate \(m_2 = 1/n \sum_{i = 1}^n ((X_i - \bar{X})^2\) for a vector X.
X
naive biased fourth central moment estimate \(m_4 = 1/n \sum_{i = 1}^n ((X_i - \bar{X})^4\) for a vector X.
sample size.
Other unbiased estimates (one-sample): uM2(), uM2M3(), uM2M4(), uM2pow3(), uM3(), uM3pow2(), uM4(), uM5(), uM6()
uM2()
uM2M3()
uM2M4()
uM2pow3()
uM3()
uM3pow2()
uM4()
uM5()
uM6()
n <- 10 smp <- rgamma(n, shape = 3) m <- mean(smp) for (j in 2:4) { m <- c(m, mean((smp - m[1])^j)) } uM2pow2(m[2], m[4], n)
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