uM2pow3pool: Pooled central moment estimates - two-sample

Description Usage Arguments Value See Also Examples

View source: R/M2pow3two.R

Description

Calculate pooled unbiased estimates of central moments and their powers and products.

Usage

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uM2pow3pool(m2, m3, m4, m6, n_x, n_y)

Arguments

m2

naive biased variance estimate m[2] = mean(c((X - X-bar)^2, (Y - Y-bar)^2)) for vectors X and Y.

m3

naive biased third central moment estimate m[3] = mean(c((X - X-bar)^3, (Y - Y-bar)^3)) for vectors X and Y.

m4

naive biased fourth central moment estimate m[4] = mean(c((X - X-bar)^4, (Y - Y-bar)^4)) for vectors X and Y.

m6

naive biased sixth central moment estimate m[6] = mean(c((X - X-bar)^6, (Y - Y-bar)^6)) for vectors X and Y.

n_x

number of observations in the first group.

n_y

number of observations in the second group.

Value

Pooled estimate of cubed variance central moment μ[2]^3, where μ[2] is a variance.

See Also

Other pooled estimates (two-sample): uM2M3pool, uM2M4pool, uM2pool, uM2pow2pool, uM3pool, uM3pow2pool, uM4pool, uM5pool, uM6pool

Examples

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nx <- 10
ny <- 8
shp <- 3
smpx <- rgamma(nx, shape = shp) - shp
smpy <- rgamma(ny, shape = shp)
mx <- mean(smpx)
my <- mean(smpy)
m  <- numeric(6)
for (j in 2:6) {
  m[j] <- mean(c((smpx - mx)^j, (smpy - my)^j))
}
uM2pow3pool(m[2], m[3], m[4], m[6], nx, ny)

innager/Umoments documentation built on June 24, 2021, 8:23 p.m.