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Calculate pooled unbiased estimates of central moments and their powers and products.
uM2pool(m2, n_x, n_y)
Pooled variance estimate.
naive biased variance estimate \(m_2 = 1/(n_x + n_y) \sum_{i = 1}^{n_x} ((X_i - \bar{X})^2 + \sum_{i = 1}^{n_y} ((Y_i - \bar{Y})^2\) for vectors X and Y.
X
Y
number of observations in the first group.
number of observations in the second group.
Other pooled estimates (two-sample): uM2M3pool(), uM2M4pool(), uM2pow2pool(), uM2pow3pool(), uM3pool(), uM3pow2pool(), uM4pool(), uM5pool(), uM6pool()
uM2M3pool()
uM2M4pool()
uM2pow2pool()
uM2pow3pool()
uM3pool()
uM3pow2pool()
uM4pool()
uM5pool()
uM6pool()
nx <- 10 ny <- 8 shp <- 3 smpx <- rgamma(nx, shape = shp) - shp smpy <- rgamma(ny, shape = shp) m2 <- mean(c((smpx - mean(smpx))^2, (smpy - mean(smpy))^2)) uM2pool(m2, nx, ny)
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